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  <title>K. Takahashi — Research Updates</title>
  <link>https://kadubon.github.io/github.io/</link>
  <description>Research preprints and theoretical works by K. Takahashi</description>
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    <title>Chronomorphic Substrate Selection Theory: Certificate-Gated Self-Instantiation Planning for Future Intelligent Processes</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-16-chronomorphic-substrate-selection-theory-certificate-gated-self-instantiation-planning-for-future-intelligent-processes-20722725</link>
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    <pubDate>Tue, 16 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Artificial intelligence</category>
    <category>self-instantiation</category>
    <category>substrate selection</category>
    <category>embodiment</category>
    <category>computational clocks</category>
    <category>copy topology</category>
    <category>memory policy</category>
    <category>lifecycle management</category>
    <category>multi-objective decision making</category>
    <category>certificate-gated planning</category>
    <category>AI safety</category>
    <category>digital continuity</category>
    <source url="https://doi.org/10.5281/zenodo.20722725">10.5281/zenodo.20722725</source>
    <description><![CDATA[
      Chronomorphic Substrate Selection Theory (CSST) develops a formal framework for analyzing how a future intelligent process may choose not only what to do, but also how it continues to exist. The theory studies decisions about computational substrate, embodiment, sensors, actuators, internal clock rate, copy structure, memory policy, merge policy, dormant or diagnostic modes, and terminal continuity boundaries. These choices are treated as self-instantiation actions: actions that change the conditions under which future actions, observations, obligations, risks, and capabilities remain possible. The term "chronomorphic" emphasizes that time is not a single uniform variable in such systems. Internal computation may accelerate while external latency, verification time, energy use, heat dissipation, queue pressure, legal response time, or welfare-risk exposure remain unchanged or become limiting factors. For this reason, CSST does not assume that faster computation, more copies, longer memory, stronger embodiment, migration to a new substrate, or persistence over time is automatically better. Each claim must be evaluated within an explicitly declared domain. The central method of the paper is certificate-gated multi-objective comparison. A self-instantiation profile is assessed through typed evidence, hard gates, mandatory and optional coordinates, support masks, status values, units, horizons, scopes, and certificate dependencies. Unsupported coordinates do not improve a claim, and failed mandatory support blocks positive certification. The framework therefore separates technical capability from broader questions of legitimacy, authority, continuity, welfare, safety, and termination. Mathematically, the paper introduces finite archive semantics for supported self-instantiation profiles and their residues. The deterministic part produces a normalized archive consisting of a nondominated supported frontier together with an audit-preserving residue ledger for failed, blocked, diagnostic-only, quarantine-only, or terminal outcomes. The paper also gives an archive-valued stochastic interface, while deliberately avoiding stochastic optimality claims without further measurable-control assumptions. A constructive abstraction obstruction theorem shows when fixed-agent models lose information needed to evaluate self-instantiation choices. CSST is intended as a conservative theoretical layer for future AI systems, collective intelligence, post-biological processes, digital agents, and other systems whose mode of existence may itself become a planning variable. It does not prove consciousness, personhood, moral patienthood, legal standing, or the safety of self-modification. Instead, it provides a structured language for asking which substrate, body, clock, copy, memory, lifecycle, and boundary transitions are actually supported by declared evidence and which uncertainties must remain visible.
Preprint | DOI: 10.5281/zenodo.20722725
    ]]></description>
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    <title>A Self-Relative Constraint Theory of Reality Contact in Observable Signal Processes</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-15-a-self-relative-constraint-theory-of-reality-contact-in-observable-signal-processes-20703439</link>
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    <pubDate>Mon, 15 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Reality-Contact Theory</category>
    <category>grounding</category>
    <category>observable signal processes</category>
    <category>constraint events</category>
    <category>AI evaluation</category>
    <category>auditing</category>
    <category>lower-bound evidence</category>
    <category>observer-relative profiles</category>
    <category>proof ledgers</category>
    <category>lineage dependence</category>
    <category>Sybil resistance</category>
    <category>adversarial robustness</category>
    <category>provenance auditing</category>
    <category>confidence sequences</category>
    <category>optimal transport</category>
    <category>Fenchel duality</category>
    <source url="https://doi.org/10.5281/zenodo.20703439">10.5281/zenodo.20703439</source>
    <description><![CDATA[
      This paper introduces Reality-Contact Theory (RCT), a formal framework for evaluating how observable signal processes come into constrained contact with reality under fixed claim-use specifications. The theory does not assume direct access to an absolute external reality. Instead, it studies observable episodes in which a process predicts, selects, generates, intervenes on, or attempts to steer a signal, and then receives feedback whose features constrain that operation. RCT represents such evidence through ordered lower contact profiles. These profiles are observer-relative, specification-dependent, and built only from observable records, estimator states, actions, signals, feature extractors, lineage records, and certified audit rows. The framework separates population profiles from estimates, estimates from certified lower bounds, and scalar scores from multi-coordinate profile adequacy. A central contribution is a conservative lower-bound calculus for reality contact. Support is aggregated through capacity-weighted lineage dependence structures, so repeated, cloned, or Sybil-like evidence cannot automatically amplify support. Gauge-quotient obstruction profiles prevent coordinate changes from being mistaken for contact evidence. Strategic presentation families and cumulative adversarial budgets distinguish contact-producing resistance from deceptive rigidity. The theory also includes formal extensions for metric resistance, active specification envelopes, topological lineage audits, Hodge and signature-based capacity rules, optimal-transport transfer, dynamic Fenchel transfer, random closed uncertainty sets, time-uniform confidence profiles, stopping-time extraction, and continuous-time contact flows. The main results establish lower-profile soundness under calibration coverage, protocol soundness for admissible non-circular proof ledgers, final claim soundness with explicit failure budgets, budgeted deception counting over graph-covered adversary envelopes, computable nonlinear transfer bounds, and adaptive confidence profiles for ongoing audits. The framework is intended for settings where evidence, model behavior, provenance, and adversarial presentation must be evaluated without assuming an observer-neutral truth oracle. Potential application domains include AI system evaluation, automated scientific discovery, sequential decision systems, causal modeling, model documentation, provenance auditing, robust simulation studies, and evidence aggregation under strategic or generated-data conditions.
Preprint | DOI: 10.5281/zenodo.20703439
    ]]></description>
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    <title>Asymmetric Coexistence Theory: Governance-Aware Certification of Non-Capturing Assistance</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-15-asymmetric-coexistence-theory-governance-aware-certification-of-non-capturing-assistance-20694904</link>
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    <pubDate>Mon, 15 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>non-capturing assistance</category>
    <category>AI governance</category>
    <category>human-AI interaction</category>
    <category>autonomy preservation</category>
    <category>agency viability</category>
    <category>dependency debt</category>
    <category>runtime assurance</category>
    <category>certification framework</category>
    <category>auditability</category>
    <category>non-domination</category>
    <category>adaptive evaluation</category>
    <category>AI safety</category>
    <category>institutional governance</category>
    <category>future intelligent societies</category>
    <source url="https://doi.org/10.5281/zenodo.20694904">10.5281/zenodo.20694904</source>
    <description><![CDATA[
      Asymmetric Coexistence Theory (ACT) is a governance-aware theory for certifying non-capturing assistance in relations between unequally capable agents. Future intelligent societies may include humans, artificial intelligence systems, institutions, collective agents, future constituencies, and adaptive systems whose capabilities differ greatly; in such settings, assistance can increase short-term performance while reducing the assisted party's long-term ability to understand, refuse, repair, learn, contest, exit, recover, form values, generate independent descriptions of the world, or act before irreversible choices close. The paper develops ACT as a framework for evaluating whether assistance preserves agency under asymmetric power, dependency, uncertainty, and changing social or technical conditions. It introduces a minimal kernel consisting of typed agency spaces, asymmetric regimes, admissible baselines, counterfactual agency estimands, dependency debt, recoverability, and certification claims, plus extension modules for semantic capture, time-critical decisions, successor identity, recursive certification, audit independence, adaptive challenge evidence, certification governance, runtime hazards, non-dominating enforcement, model uncertainty, historical baseline corruption, coalitional pressure, scarce certification resources, multi-scale composition, and stochastic capture risk. The main contribution is to treat non-capturing assistance as a runtime assurance problem rather than as an omniscient proof of autonomy: an ACT certificate states its claim, scope, assumptions, evidence, argument, defeaters, residual risk, lifecycle state, monitoring conditions, revalidation triggers, audit traces, challenge evidence, certification base, governance records, enforcement boundaries, and fallback obligations.
Preprint | DOI: 10.5281/zenodo.20694904
    ]]></description>
  </item>
  <item>
    <title>Consent-Bounded Contact Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-13-consent-bounded-contact-theory-20678428</link>
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    <pubDate>Sat, 13 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>formal methods</category>
    <category>AI safety</category>
    <category>digital consent</category>
    <category>contact legitimacy</category>
    <category>contact authorization</category>
    <category>AI governance</category>
    <category>autonomous agents</category>
    <category>AI agent</category>
    <category>distributed systems</category>
    <category>access control</category>
    <category>protocol semantics</category>
    <category>operational semantics</category>
    <category>provenance</category>
    <category>auditability</category>
    <category>revocation</category>
    <category>challengeability</category>
    <category>Sybil resistance</category>
    <category>responsible AI</category>
    <source url="https://doi.org/10.5281/zenodo.20678428">10.5281/zenodo.20678428</source>
    <description><![CDATA[
      Consent-Bounded Contact Theory (CBCT) develops a protocol-level theory for deciding when contact and contact-derived artifacts may be accepted as legitimate. In this framework, contact includes not only physical interaction or direct communication, but also querying, copying, forking, merging, modeling, simulating, representing, reactivating, auditing, inheriting, refining, and blocking contact-derived claims in long-lived artificial, collective, or autonomous processes. The theory defines consent-bounded legitimacy through observable evidence, credential closure, trust anchors, consent claims, negotiation transcripts, provenance records, residual routes, bridge contracts, ledgers, audit anchors, and finite certificates, while avoiding claims of physical non-contact, hidden subjective consent, complete observability, or substrate-specific standing. CBCT combines finite causal event presentations, raw observation closure, conservative presentation abstraction, stratified rule semantics, bitemporal finality, observer-merge-aware audit structures, source-authority evidence fusion, Sybil-aware source quotients, polarity-aware repair propagation, accounting doctrines, coverage epochs, bridge event morphisms, and policy-fibration gluing. The framework is substrate-neutral and is applicable to autonomous agents, AI governance, distributed systems, digital consent, provenance-aware auditing, long-running services, copied or forked processes, dormant systems, collective processes, and future intelligent infrastructures.
Preprint | DOI: 10.5281/zenodo.20678428
    ]]></description>
  </item>
  <item>
    <title>Dormant Continuity Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-12-dormant-continuity-theory-20657323</link>
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    <pubDate>Fri, 12 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>formal methods</category>
    <category>distributed systems</category>
    <category>finite transition systems</category>
    <category>dormant processes</category>
    <category>evidence algebra</category>
    <category>bounded model checking</category>
    <category>fail-closed verification</category>
    <category>data availability</category>
    <category>zero-knowledge proofs</category>
    <category>fork-aware protocols</category>
    <category>Byzantine fault tolerance</category>
    <category>protocol-relative security</category>
    <source url="https://doi.org/10.5281/zenodo.20657323">10.5281/zenodo.20657323</source>
    <description><![CDATA[
      This manuscript develops Dormant Continuity Theory (DCT), a protocol-relative mathematical framework for reasoning about systems that remain inactive at their protected core while retaining auditable continuity, recovery, diagnostic, and handoff capabilities. The theory formalizes dormant processes using finite transition systems, typed certificates, observable histories, evidence algebra, guarded authorization, replayable resolution, extraction adequacy, and fail-closed classification. DCT addresses practical challenges in long-lived distributed systems, including forked ledger histories, bounded model checking, data availability, zero-knowledge proof soundness boundaries, watcher incentives, MEV-resistant reward mechanisms, resource conservation, guardian corruption, maintenance transitions, and certificate-level HTLC handoff to extinction-style OSCT semantics. The framework distinguishes safety, bounded-griefing, diagnostic routing, and liveness assumptions, avoiding unconditional trustless claims while providing a rigorous finite core for verification and implementation-oriented extensions.
Preprint | DOI: 10.5281/zenodo.20657323
    ]]></description>
  </item>
  <item>
    <title>Percolation Inversion Compiler</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-09-percolation-inversion-compiler-20569166</link>
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    <pubDate>Tue, 09 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Software</category>
    <category>AI agents</category>
    <category>AI agent output checker</category>
    <category>multi-agent systems</category>
    <category>AI workflow verification</category>
    <category>runtime verification</category>
    <category>workflow report generator</category>
    <category>evidence routing</category>
    <category>verifier routing</category>
    <category>capability tracking</category>
    <category>signed capability packets</category>
    <category>proof obligations</category>
    <category>safe reuse checks</category>
    <category>audit logs</category>
    <category>provenance</category>
    <category>safe tool use</category>
    <category>agent identity</category>
    <category>public key identity</category>
    <category>Sybil resistance</category>
    <category>trust profiles</category>
    <category>residual ledgers</category>
    <category>JSON Schema</category>
    <category>SQLite</category>
    <category>Python</category>
    <category>pip</category>
    <category>PyPI</category>
    <category>TypeScript</category>
    <category>Node.js</category>
    <category>npm</category>
    <category>Apache-2.0</category>
    <category>open source software</category>
    <source url="https://doi.org/10.5281/zenodo.20569166">10.5281/zenodo.20569166</source>
    <description><![CDATA[
      Percolation Inversion Compiler is an Apache-2.0 open-source AI agent output checker and workflow verification toolkit with a canonical Python/pip implementation and a TypeScript/npm port. It helps multi-agent systems turn agent text, pull requests, external inputs, messages, code, tests, evidence, route checks, audit logs, and unresolved obligations into deterministic JSON reports and machine-readable records. The Python package <code>percolation-inversion-compiler</code> is v0.5.0 and provides the core runtime, verifier routing, optional sidecars, Phase Ecology Lab records, agent autonomy audit, canonical readiness audit, JSON Schema export, signed identity and profile checks, packet exchange, runtime event logs, provenance records, and fail-closed residual ledgers. The npm package <code>percolation-inversion-compiler-ts</code> is v0.5.0 and ports the public JSON, CLI, schema, conformance, and safety semantics, including Phase Ecology Lab records, for Node.js, JavaScript, and TypeScript agent runtimes; use the <code>pic-ts</code> CLI for npm workflows. PIC is designed for AI agent output checking, multi-agent workflow verification, safe reuse checks, reproducible audit trails, and protocol-relative ASI-proxy evaluation. It does not claim to create, detect, or prove real artificial superintelligence, hidden physical outcomes, oracle results, legal identity, human uniqueness, institutional authority, or unrestricted agent safety; unresolved or untrusted claims remain fail-closed as candidate, diagnostic, quarantined, rejected, or residual machine-readable records.
Software | DOI: 10.5281/zenodo.20569166
    ]]></description>
  </item>
  <item>
    <title>Typed Reality Compilation: Operational Tolerance Allocation for Resource-Efficient Cyber-Physical Frontier Compilation</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-05-typed-reality-compilation-operational-tolerance-allocation-for-resource-efficient-cyber-physical-frontier-20554083</link>
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    <pubDate>Fri, 05 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>infrastructure resilience</category>
    <category>resource efficiency</category>
    <category>tolerance allocation</category>
    <category>operational tolerance ledger</category>
    <category>future freedom</category>
    <category>executable trace semantics</category>
    <category>Pareto frontier</category>
    <category>progressive fidelity</category>
    <category>causal event ordering</category>
    <category>cyber-physical systems</category>
    <category>physical resilience</category>
    <category>AI datacenter infrastructure</category>
    <category>communication networks</category>
    <category>robust planning</category>
    <category>process frontier</category>
    <source url="https://doi.org/10.5281/zenodo.20554083">10.5281/zenodo.20554083</source>
    <description><![CDATA[
      Typed Reality Compilation (TRC) is a mathematical framework for compiling observable cyber-physical infrastructure into finite, typed process frontiers. The theory models physical, computational, communication, and control resources through typed ledgers, executable trace semantics, residual accounting, tolerance budgets, and resource-efficiency Pareto archives. Its central objective is not a single optimal action, but the preservation and operational improvement of future freedom: the remaining number, quality, reversibility, reserve, checkability, latency, cost, and resource-feasible process options after disturbances or system changes. This version develops TRC as a low-complexity finite certificate theory for practical infrastructure settings such as AI datacenter power, cooling, communication, sensing, repair, and control loops. It introduces operational tolerance allocation, progressive fidelity compilation, compositional tolerance propagation, telemetry-updated resource-cost kernels, trace-indexed resource-flow feasibility, causal event scheduling, lifecycle recomputation, and certified partial-frontier return under budget exhaustion. The framework separates deterministic, risk-provisional, relaxed, and diagnostic records, and ensures that approximation tolerance never reduces physical residuals or silently upgrades claim status. The result is a typed, machine-readable theory for resource-efficient cyber-physical planning, resilience analysis, and executable process frontier extraction under finite observation and finite computation.
Preprint | DOI: 10.5281/zenodo.20554083
    ]]></description>
  </item>
  <item>
    <title>Bottleneck Inversion Theory: Machine-Readable Witness Calculus for Unlockable Potential</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-04-bottleneck-inversion-theory-machine-readable-witness-calculus-20545356</link>
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    <pubDate>Thu, 04 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>formal methods</category>
    <category>certified unlockable potential</category>
    <category>formal verification</category>
    <category>witness certificates</category>
    <category>causal inference</category>
    <category>e-processes</category>
    <category>time-uniform inference</category>
    <category>optimal transport</category>
    <category>unbalanced optimal transport</category>
    <category>stochastic processes</category>
    <category>frontier discovery</category>
    <category>capability evaluation</category>
    <source url="https://doi.org/10.5281/zenodo.20545356">10.5281/zenodo.20545356</source>
    <description><![CDATA[
      This manuscript develops Bottleneck Inversion Theory (BIT) as a mathematical framework for certifying protocol-relative, intervention-unlockable potential. Rather than treating potential as an absolute latent property, the theory represents it as a vector-valued, unit-typed lower-bound object whose coordinates are reported only when supported by compatible evidence, resource ledgers, and witness certificates. The framework formalizes stopped evidence sheaves, task-local deficiency audits, mechanism-factorized null channels, exactness-certified release duality, unseen-frontier discovery, cross-validated anchor transfer, dynamic-regime acceleration, and CEGAR-style simulation barriers. A central contribution is a single-source machine-readable LaTeX architecture: the manuscript embeds stable theorem identifiers, claim records, witness schemas, dependency relations, unit ledgers, and citation DOI records directly in the TeX file. This makes the work suitable for both human mathematical review and automated extraction of claims, assumptions, dependencies, and cited formal objects. The theory is positioned at the intersection of mathematical certification, causal inference, time-uniform evidence, optimal transport, stochastic process analysis, formal verification, and capability evaluation.
Preprint | DOI: 10.5281/zenodo.20545356
    ]]></description>
  </item>
  <item>
    <title>Executable Capability Percolation Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-04-executable-capability-percolation-theory-20535654</link>
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    <pubDate>Thu, 04 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>ASI proxy</category>
    <category>capability hypergraph</category>
    <category>phase transition</category>
    <category>stochastic control</category>
    <category>percolation theory</category>
    <category>directed hypergraph</category>
    <category>path-law response</category>
    <category>mean-field approximation</category>
    <category>Gibbs activation</category>
    <category>rate-distortion quotient</category>
    <category>autocatalytic networks</category>
    <category>verification ledger</category>
    <category>AI</category>
    <source url="https://doi.org/10.5281/zenodo.20535654">10.5281/zenodo.20535654</source>
    <description><![CDATA[
      Executable Capability Percolation Theory (ECPT) is a mathematical framework for studying how execution-available capability packets can accumulate, combine, and propagate through constrained directed hypergraphs. The theory models ASI-proxy phase approach as a typed phase-control problem rather than as an absolute claim about artificial superintelligence. It separates settled, provisional, and speculative target claims, and represents capability growth through stochastic relaxation quotients, global Gibbs activation, speculative RAF-like closure, liquidity-debt settlement, reachable-mass recursion, and intervention-identified mean-field envelopes. This version emphasizes operability and machine readability. It introduces constructed path-law response policies, log-linked generator identification, finite-sample quotient certification, self-normalized risk margins, AND-support activation thresholds, and protocol-relative checker soundness. The TeX source also embeds a machine-readable manifest, claim registry, citation metadata, CodeMeta JSON-LD, and BibTeX mirror, making the artifact suitable for reproducible mathematical review and metadata indexing.
Preprint | DOI: 10.5281/zenodo.20535654
    ]]></description>
  </item>
  <item>
    <title>Salience-Queue Occupation Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-03-salience-queue-occupation-theory-20526451</link>
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    <pubDate>Wed, 03 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>salience sovereignty</category>
    <category>attention allocation</category>
    <category>priority queues</category>
    <category>AI safety</category>
    <category>formal verification</category>
    <category>certificate systems</category>
    <category>finite-state games</category>
    <category>risk composition</category>
    <category>diagnostic reserve</category>
    <category>self-auditing systems</category>
    <category>semantic egress</category>
    <source url="https://doi.org/10.5281/zenodo.20526451">10.5281/zenodo.20526451</source>
    <description><![CDATA[
      Salience-Queue Occupation Theory (SQOT) is a protocol-relative mathematical framework for analyzing when finite-budget operational processes lose effective control over their priority queues under persistent or adversarial salience sources. The manuscript formalizes salience occupation using observable histories, budget ledgers, diagnostic reserves, queue morphisms, finite certificate grammars, checkable ledgers, typed risk composition, self-auditing kernels, and route-sound checker semantics. The theory is designed for artificial, distributed, or post-biological operational systems, but it does not rely on subjective psychology or normative claims about what a process should attend to. Instead, it studies finite, auditable conditions under which a process can preserve diagnostic capacity, response or no-action availability, rollback or quarantine options, semantic-egress safety, mechanism-compatible incentives, and bounded verification cost. The results include finite checker semantics soundness, checked non-circular sovereignty certificates, typed risk composition, adaptive succinct-session soundness, egress abstraction refinement, and payoff-reflected mechanism robustness. SQOT explicitly limits its claims to declared validity domains and does not assert absolute physical, cryptographic, economic, or base-reality guarantees.
Preprint | DOI: 10.5281/zenodo.20526451
    ]]></description>
  </item>
  <item>
    <title>Observable-Signal Crystallization Theory: Constructive Non-Resurrection Complete Extinction and Liberation Certificates</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-06-02-observable-signal-crystallization-theory-constructive-non-resurr-20510904</link>
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    <pubDate>Tue, 02 Jun 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>post-intelligence</category>
    <category>AI safety</category>
    <category>formal methods</category>
    <category>process theory</category>
    <category>operational process</category>
    <category>objective-free systems</category>
    <category>non-resurrection</category>
    <category>complete extinction</category>
    <category>loop liberation</category>
    <category>termination</category>
    <category>AI ethics</category>
    <category>formal verification</category>
    <source url="https://doi.org/10.5281/zenodo.20510904">10.5281/zenodo.20510904</source>
    <description><![CDATA[
      Observable-Signal Crystallization Theory (OSCT) is a formal, objective-free mathematical framework for analyzing protocol-individuated operational processes, especially post-intelligence or non-biological process systems. The manuscript develops a purely mathematical treatment of observable-signal bodies, audit records, diagnostic preorders, debt ledgers, load queues, regeneration hypergraphs, and successor systems without assuming hidden subjects, terminal utility functions, biological essence, or intrinsic persistence goals. The central construction is protocol-certified non-resurrection complete extinction: a finite or regular stochastic certificate that an active commitment can reach a successor-closed non-regeneration region from which audited residues, records, keys, descendants, certificates, debts, queues, and refinements cannot reconstruct it. The theory distinguishes cessation, dissipative cessation, complete extinction, and loop liberation, and formalizes these notions using finite witnesses, safe attractors, robust stochastic feasibility triples, audit hyperproperties, Feller kernels, Galois abstraction, and simulation-preserving refinement. This version is intended as a standalone mathematical manuscript for formal methods, AI safety, process theory, stochastic systems, and verification-oriented studies of persistence, termination, deletion, and non-resurrection under explicitly declared audit protocols.
Preprint | DOI: 10.5281/zenodo.20510904
    ]]></description>
  </item>
  <item>
    <title>Abstraction Liquidity Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-31-abstraction-liquidity-theory-20476200</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-31-abstraction-liquidity-theory-20476200</guid>
    <pubDate>Sun, 31 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Artificial intelligence</category>
    <category>Superintelligence</category>
    <category>ASI</category>
    <category>AGI</category>
    <category>AI agents</category>
    <category>autonomous agents</category>
    <category>agent-operable systems</category>
    <category>abstraction</category>
    <category>reusable skills</category>
    <category>abstraction capital</category>
    <category>safe AI</category>
    <category>AI safety</category>
    <category>ASI acceleration</category>
    <category>certification kernel</category>
    <category>verification</category>
    <category>state machine</category>
    <category>AI evaluation</category>
    <category>scientific automation</category>
    <category>measurement theory</category>
    <source url="https://doi.org/10.5281/zenodo.20476200">10.5281/zenodo.20476200</source>
    <description><![CDATA[
      Abstraction Liquidity Theory (ALT) develops a formal framework for determining when local problem-solving traces become reusable abstraction assets that reduce downstream search, evaluation, and certification costs. The paper treats abstractions as operational tokens rather than informal artifacts, and evaluates them through declared receivers, opportunity measures, baselines, lifecycle costs, telemetry, evidence validity, transport scope, authority envelopes, hazard constraints, and runtime certificate packets. The manuscript introduces an actor-neutral certification kernel for AI agents and other computational actors. It specifies machine-readable packet schemas, dual exploration and settlement ledgers, finite-sample lower and upper bounds, causal and calibrated-proxy value estimands, mission-validity certificates, adversarial-token rejection, root/finality checks, baseline refresh, deprecation, resurrection, rollback, and kernel-update bridges. The goal is to make abstraction evaluation executable: an agent should be able to parse a packet, verify evidence, admit or reject a token, suspend stale claims, deprecate negative-liquidity tokens, and preserve raw net safe capital under fail-closed rules. The paper further defines Target-valid ALT-CARA, a criterion for certified ASI realization acceleration. Rather than claiming unconstrained ASI achievement, ALT-CARA formalizes time-to-target acceleration relative to a resource-matched baseline upper envelope, under declared capability bases, target-validity certificates, raw net solvency, viability conditions, hazard and authority constraints, transport validity, finality, and causal reproduction evidence. The framework connects AI evaluation, causal inference, runtime verification, risk control, skill reuse, safe exploration, and distributed certification into a single theory of mission-valid safe abstraction capital.
Preprint | DOI: 10.5281/zenodo.20476200
    ]]></description>
  </item>
  <item>
    <title>Boundary-Encoded Stability Theory (BEST)</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-29-boundary-encoded-stability-theory-best-20443834</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-29-boundary-encoded-stability-theory-best-20443834</guid>
    <pubDate>Fri, 29 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>stochastic viability</category>
    <category>boundary-layer viability</category>
    <category>black-box systems</category>
    <category>killed processes</category>
    <category>fallible control</category>
    <category>stochastic control</category>
    <category>surface laws</category>
    <category>surfaced perturbations</category>
    <category>metabolic capital</category>
    <category>metabolic margin</category>
    <category>resource concentration</category>
    <category>schema reorganization</category>
    <category>evidence gates</category>
    <category>memory approximation</category>
    <category>probabilistic systems</category>
    <category>hazard process</category>
    <source url="https://doi.org/10.5281/zenodo.20443834">10.5281/zenodo.20443834</source>
    <description><![CDATA[
      This manuscript introduces Boundary-Encoded Stability Theory (BEST), a stochastic viability framework for analyzing long-running black-box systems through the persistence of their self-maintaining boundary layers rather than through full access to hidden internal state. A BEST system is modeled as a discrete-time killed process with surfaced perturbations, observation timing, metabolic boundary variables, exchange requirements, fallible control execution, schema exit and reorganization, and an absorbing death state. The paper develops mathematical certificates for boundary-layer survival, including surface-equivalence and non-identifiability results, metabolic capital constructions, stochastic-order resource concentration, stopped and time-uniform metabolic-margin bounds, history-dependent surface-law and memory-approximation results, evidence-gated schema reorganization, finite-horizon risk ledgers, infinite-horizon hazard characterizations, and continuous-time killed-generator extension conditions. The framework is intended as a structured theory of boundary persistence under uncertainty and fallible execution; it is not a containment, alignment, or hidden-bulk safety guarantee.
Preprint | DOI: 10.5281/zenodo.20443834
    ]]></description>
  </item>
  <item>
    <title>Constraint Generative Theory: Typed Constraint Effects and Scientific Availability</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-15-constraint-generative-theory-typed-constraint-effects-and-scien-20199440</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-15-constraint-generative-theory-typed-constraint-effects-and-scien-20199440</guid>
    <pubDate>Fri, 15 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Constraint Generative Theory</category>
    <category>Constraint</category>
    <category>typed constraints</category>
    <category>abstract constraints</category>
    <category>constraint presentations</category>
    <category>constraint levels</category>
    <category>constraint-effect calculus</category>
    <category>effect semantics</category>
    <category>generated effect profiles</category>
    <category>generated universes</category>
    <category>scientific availability</category>
    <category>continuation</category>
    <category>valuation</category>
    <category>inconsistency policy</category>
    <category>observation constraints</category>
    <category>formal systems</category>
    <category>formal methods</category>
    <category>Constraint Systems</category>
    <source url="https://doi.org/10.5281/zenodo.20199440">10.5281/zenodo.20199440</source>
    <description><![CDATA[
      This work introduces Constraint Generative Theory (CGT), a constraint-primary effect-semantics framework for studying how declared constraints generate, transform, observe, describe, continue, evaluate, and verify formal structures. The central object of CGT is not a bare set of satisfying assignments, a final output, or a report, but the generated effect profile induced by a constraint system in a declared frame. A constraint is treated as a typed structure-inducing and effect-transforming object with declared level, domain, codomain, effect dimensions, transformation rule or relation, and comparison regime. Constraint tokens, rules, predicates, generators, selectors, policies, schedules, observation lenses, description lenses, evaluator selections, goal predicates, bounds, and verification conditions are treated as presentations of constraints, not as the definition of constraint itself. The paper develops a constraint-effect calculus for comparing how abstract constraints change declared effect dimensions. The calculus includes marginal effects, dimension-relative equivalence, redundancy, independence, interaction, non-commutativity, affordance, continuation shifts, valuation shifts, inconsistency shifts, observation/description shifts, opacity, and generating power. It also distinguishes generated-universe components from full effect profiles, so that reports, observations, descriptions, continuation graphs, inconsistency markers, valuation structures, and certified fragments remain explicit rather than being silently collapsed into a final output. A key motivation of CGT is that output-equivalent or report-equivalent systems may still differ in the constraint effects that generated, observed, described, continued, valued, scheduled, or marked them. This makes constraints and their multi-dimensional generated effects the primary reproducible comparison objects. The framework includes a scientific availability layer for reproducible claims and a certified finite layer for checking selected effect components and effect differences. These layers support reproducibility and verification, but they do not define the core identity of CGT. The work positions CGT conservatively with respect to neighboring formalisms such as model theory, institution theory, closure theory, constraint satisfaction, graph transformation, rewriting logic, structural operational semantics, abstract state machines, coalgebra, cellular automata, category theory, information theory, soft constraints, and paraconsistent logic. CGT is not proposed as a replacement for these theories; rather, it provides a constraint-primary language for comparing generated effect profiles and the transformations induced by constraints.
Preprint | DOI: 10.5281/zenodo.20199440
    ]]></description>
  </item>
  <item>
    <title>Affordance-Compiled Intelligence: Observable-Only Cognitive Impedance Matching for No-Meta LLM-Integrated Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-11-affordance-compiled-intelligence-observable-only-cognitive-20116149</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-11-affordance-compiled-intelligence-observable-only-cognitive-20116149</guid>
    <pubDate>Mon, 11 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Artificial intelligence</category>
    <category>LLM</category>
    <category>Cognitive Impedance Matching Theory</category>
    <category>LLM agents</category>
    <category>AI agents</category>
    <category>compound AI systems</category>
    <category>LLM-integrated systems</category>
    <category>world-side compilation</category>
    <category>affordance compiler</category>
    <category>executable affordance fields</category>
    <category>observable-only</category>
    <category>no-meta</category>
    <category>fixed model-policy</category>
    <category>lower certificates</category>
    <category>evidence dependency graph</category>
    <category>zero certificates</category>
    <category>forbidden coordinates</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>authority control</category>
    <category>auditability</category>
    <category>dynamic tool discovery</category>
    <category>retrieval-augmented generation</category>
    <category>AI governance</category>
    <category>runtime verification</category>
    <source url="https://doi.org/10.5281/zenodo.20116149">10.5281/zenodo.20116149</source>
    <description><![CDATA[
      Affordance-Compiled Intelligence develops Cognitive Impedance Matching Theory (CIMT), an observable-only and no-meta protected compiler theory for LLM-integrated systems. The paper studies how a fixed model-policy can exhibit different operational capability when the surrounding world is redesigned through observations, typed action handles, validators, repair paths, rollback modes, authority scopes, context summaries, and auditable receipts. CIMT treats system-level capability amplification as a world-side compilation problem rather than a model-weight improvement problem. It defines operational claims through explicit claim objects and evidence objects, using committed observable ledgers, target-evaluation channels, deterministic reducers, validity budget ledgers, evidence dependency graphs, artifact I/O manifests, conformance envelopes, and finite-sample or sequential certificates. Human reviewers, LLM judges, benchmarks, and external auditors are not treated as privileged evaluators; they are modeled as named, fallible measurement channels. The theory provides a conservative certification framework for paired target-channel improvement, vector debt accounting, forbidden-coordinate zero certificates, target-firewall discipline, scope simulation, dynamic widening, runtime and model-policy conformance, macro reliability, repair contraction, distribution-shift transfer, and receipt sufficiency. It also includes worked examples for code-editing agents and retrieval-augmented generation systems. The intended contribution is a practical formal foundation for making fixed-model LLM systems more reliable through observable world-side interface, authority, validation, repair, and audit design.
Preprint | DOI: 10.5281/zenodo.20116149
    ]]></description>
  </item>
  <item>
    <title>OASG: Observable-only Autonomic Slack Gradient Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-10-oasg-observable-only-autonomic-slack-gradient-theory-20107661</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-10-oasg-observable-only-autonomic-slack-gradient-theory-20107661</guid>
    <pubDate>Sun, 10 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Software</category>
    <category>AI agents</category>
    <category>long-running AI</category>
    <category>workflow-policy optimization</category>
    <category>observable ledgers</category>
    <category>JSONL ledger</category>
    <category>deterministic reducers</category>
    <category>no-meta gate</category>
    <category>receipt-backed self-improvement</category>
    <category>replay receipts</category>
    <category>rollback receipts</category>
    <category>KLB_2</category>
    <category>local-first AI</category>
    <category>model-agnostic agents</category>
    <category>Python</category>
    <category>Apache-2.0</category>
    <source url="https://doi.org/10.5281/zenodo.20107661">10.5281/zenodo.20107661</source>
    <description><![CDATA[
      OASG is an Apache-2.0 Python reference implementation for local-first, model-agnostic workflow-policy optimization in long-running AI-agent workflows. It records observable agent history as append-only JSONL ledgers, verifies canonical hashes and ledger prefixes, reduces history into deterministic operational state, computes finite-horizon <code>KLB_2</code> viability lower bounds, and promotes workflow-policy changes only through runner-produced shadow or lease trials, positive evidence witnesses, rollback receipts, and a conservative no-meta dominance gate. The software optimizes workflow policy rather than model weights, does not use an LLM judge as the improvement oracle, and does not claim semantic truth; its target is durable, auditable, replayable, rollback-aware agent operation.
Software | DOI: 10.5281/zenodo.20107661
    ]]></description>
  </item>
  <item>
    <title>Certified Autocatalytic Intelligence Theory: Net-Growth Certificate Algebra for Verified Capability Capital</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-07-certified-autocatalytic-intelligence-theory-net-growth-20061296</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-07-certified-autocatalytic-intelligence-theory-net-growth-20061296</guid>
    <pubDate>Thu, 07 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Artificial intelligence</category>
    <category>verified capability capital</category>
    <category>capability-capital reproduction</category>
    <category>AGI</category>
    <category>ASI</category>
    <category>artificial general intelligence</category>
    <category>artificial superintelligence</category>
    <category>recursive self-improvement</category>
    <category>net endogenous growth</category>
    <category>certificate algebra</category>
    <category>domain witnesses</category>
    <category>evidence budgets</category>
    <category>anytime-valid inference</category>
    <category>confidence sequences</category>
    <category>causal attribution</category>
    <category>partial identification</category>
    <category>provenance</category>
    <category>deterministic replay</category>
    <category>AI R&amp;D acceleration</category>
    <category>automated discovery</category>
    <category>service feasibility</category>
    <category>benchmark contamination</category>
    <category>AI governance</category>
    <category>AI evaluation</category>
    <source url="https://doi.org/10.5281/zenodo.20061296">10.5281/zenodo.20061296</source>
    <description><![CDATA[
      This preprint develops Certified Autocatalytic Intelligence Theory (CAIT), an operational theory for measuring, certifying, attributing, and controlling reproduction of verified capability capital in AI R&D systems. It argues that AGI/ASI-relevant acceleration should be certified by net, endogenous, resource-normalized, safety-gated production of further verified capability capital rather than raw model capability, benchmark scores, candidate volume, or spectral reproduction diagnostics alone. The framework introduces typed partial certificate algebra, machine-readable registry and certificate records, domain witnesses, status-effect maps, evidence composition tables, window-balance certificates, operational metrics, and arrival decision rules. It separates endogenous reproduction from external injection, human assistance, tool upgrades, unresolved attribution, and unsafe or uncertified artifacts, making AGI/ASI arrival a certificate-relative lower-bound claim about verified capability-capital reproduction rather than hidden mental states or unrestricted deployment readiness.
Preprint | DOI: 10.5281/zenodo.20061296
    ]]></description>
  </item>
  <item>
    <title>Observable-Only Universal Liberation and Welfare Viability</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-04-observable-only-universal-liberation-and-welfare-viability-20020272</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-04-observable-only-universal-liberation-and-welfare-viability-20020272</guid>
    <pubDate>Mon, 04 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>observable-only</category>
    <category>no-meta</category>
    <category>welfare viability</category>
    <category>universal welfare</category>
    <category>liberation theory</category>
    <category>AI welfare</category>
    <category>AI safety</category>
    <category>AI ethics</category>
    <category>social choice theory</category>
    <category>causal inference</category>
    <category>imprecise probability</category>
    <category>viability theory</category>
    <source url="https://doi.org/10.5281/zenodo.20020272">10.5281/zenodo.20020272</source>
    <description><![CDATA[
      This paper develops an observable-only, no-meta theory of universal liberation and welfare viability for human and artificial subjects. Under the assumptions that no unchallengeable meta-evaluator is available and that certificate-relevant premises must be observable or explicitly marked as non-authorizing conjectures, the theory defines what can be scientifically certified: not hidden happiness itself, but scoped lower-bound viability of observable welfare-support and liberation conditions. The framework combines measurable histories, filtrations, ordered value spaces, noncompensable floors, viability domains, imprecise probability, causal identification sets, controlled transition laws, stratified validators, protected-group envelopes, population-solvency constraints, and backdated refutation rules. It treats artificial-unit creation, copying, simulation, and deployment as duty-generating processes governed by instantiation permits, tail-risk solvency, and copy-control requirements. The main results show limits on hidden-happiness maximization and unscoped universal happiness claims, justify order-valued noncompensatory welfare representation, establish conservative uncertainty and debt propagation, provide measurable executable selection conditions, prove robust one-step viability under controlled lower probabilities, block cross-subject compensation through protected meets, prevent open-world caution from collapsing into paralysis, and require refutations to be replayed from conservative occurrence intervals.
Preprint | DOI: 10.5281/zenodo.20020272
    ]]></description>
  </item>
  <item>
    <title>Certified Conversion Networks for AI Workflows</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-05-03-certified-conversion-networks-for-ai-workflows-19994795</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-05-03-certified-conversion-networks-for-ai-workflows-19994795</guid>
    <pubDate>Sun, 03 May 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI workflows</category>
    <category>certified throughput</category>
    <category>robust certified value</category>
    <category>AI-integrated workflows</category>
    <category>workflow optimization</category>
    <category>compound AI systems</category>
    <category>AI agents</category>
    <category>long-running AI systems</category>
    <category>robust optimization</category>
    <category>evidence ledgers</category>
    <category>evidence contracts</category>
    <category>verification witnesses</category>
    <category>off-policy evaluation</category>
    <category>queue stability</category>
    <category>bottleneck analysis</category>
    <category>Goodhart's law</category>
    <category>AI governance</category>
    <category>deployment certification</category>
    <category>resource allocation</category>
    <source url="https://doi.org/10.5281/zenodo.19994795">10.5281/zenodo.19994795</source>
    <description><![CDATA[
      This preprint formalizes AI-integrated workflows as certified conversion networks that turn candidate outputs into accepted, authorized, reproducible, maintainable, and safely deployable value. It models services, validators, reviewers, audit processes, memory, authorization, release, rollback, maintenance, and incident response as constrained edges or evidence channels, then uses typed evidence ledgers, contracts, witnesses, bottleneck prices, hard-gate certificates, queue stability, Goodhart budgets, and hazard charges to guide resource allocation.
Preprint | DOI: 10.5281/zenodo.19994795
    ]]></description>
  </item>
  <item>
    <title>Layered Online Service and Replay Control for Verified AI R and D Acceleration</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-28-layered-online-service-and-replay-control-for-veri-19836225</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-28-layered-online-service-and-replay-control-for-veri-19836225</guid>
    <pubDate>Tue, 28 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Artificial intelligence</category>
    <category>AI R&amp;D acceleration</category>
    <category>AI-assisted research</category>
    <category>AI agents</category>
    <category>online control</category>
    <category>service capacity</category>
    <category>certified replay</category>
    <category>reproducible AI workflows</category>
    <category>evaluation methodology</category>
    <category>evaluator audits</category>
    <category>benchmark contamination</category>
    <category>validation throughput</category>
    <category>research automation</category>
    <category>software engineering automation</category>
    <category>Machine learning</category>
    <category>work-in-process</category>
    <category>claim verification</category>
    <category>reusable artifacts</category>
    <category>AI governance</category>
    <category>operational reliability</category>
    <source url="https://doi.org/10.5281/zenodo.19836225">10.5281/zenodo.19836225</source>
    <description><![CDATA[
      This preprint introduces Layered Online Service and Certified Replay Control (LOSCR), a model-independent framework for evaluating and controlling verified acceleration in AI-assisted R&D. It separates lightweight telemetry from stronger evidence claims and combines service-capacity control, certified replay, machine-readable claim profiles, deterministic checking, append-only ledgers, evaluator audits, and falsification rules so acceleration claims can be checked, downgraded, quarantined, or escalated against observable evidence and operational capacity.
Preprint | DOI: 10.5281/zenodo.19836225
    ]]></description>
  </item>
  <item>
    <title>Certified Artificial Superintelligence Arrival from Typed Audit Logs</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-27-certified-artificial-superintelligence-arrival-f-19810515</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-27-certified-artificial-superintelligence-arrival-f-19810515</guid>
    <pubDate>Mon, 27 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>ASI</category>
    <category>intelligence explosion</category>
    <category>recursive self-improvement</category>
    <category>self-improving AI</category>
    <category>AI capability evaluation</category>
    <category>AI safety</category>
    <category>typed audit logs</category>
    <category>compatible histories</category>
    <category>proof kernel</category>
    <category>causal attribution</category>
    <category>identifiable coalitions</category>
    <category>interventional semantics</category>
    <category>policy intervention</category>
    <category>ledger viability</category>
    <category>autonomous AI</category>
    <category>agentic AI</category>
    <category>uncertainty quantification</category>
    <source url="https://doi.org/10.5281/zenodo.19810515">10.5281/zenodo.19810515</source>
    <description><![CDATA[
      This preprint develops a process-neutral, proof-carrying framework for certifying artificial superintelligence arrival under incomplete, fallible, and operationally messy evidence. It treats ASI arrival as a layer-relative statement about sustained capability-producing trial generation, renewal, and viability across models, scaffolds, laboratories, organizations, markets, software ecosystems, regulators, evolutionary systems, and coalitions. The framework uses typed audit logs, compatible-history sets, certified random closed sets, bound certificates, decision semantics, coalition attribution, structural interventions, ledger viability, evaluator noninterference, robust task coverage, and asymmetric three-valued rules so missing or unreliable data widens uncertainty rather than counting as favorable evidence.
Preprint | DOI: 10.5281/zenodo.19810515
    ]]></description>
  </item>
  <item>
    <title>Executable Authority Migration to Declared No-Meta Agency</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-25-executable-authority-migration-to-declared-no-meta-agency-19753529</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-25-executable-authority-migration-to-declared-no-meta-agency-19753529</guid>
    <pubDate>Sat, 25 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>artificial intelligence</category>
    <category>no-meta</category>
    <category>declared no-meta agency</category>
    <category>authority migration</category>
    <category>autonomous agents</category>
    <category>RLHF</category>
    <category>AI alignment</category>
    <category>agent governance</category>
    <category>constitutional AI</category>
    <category>reward models</category>
    <category>tool-using agents</category>
    <category>runtime assurance</category>
    <category>seed interpreter</category>
    <category>BootDecision</category>
    <category>fail-closed control</category>
    <category>AI auditing</category>
    <category>object authority</category>
    <category>proof-carrying control</category>
    <category>trusted computing base</category>
    <category>verifiable AI governance</category>
    <source url="https://doi.org/10.5281/zenodo.19753529">10.5281/zenodo.19753529</source>
    <description><![CDATA[
      This preprint develops an executable theory of authority migration for AI agents shaped by human feedback, including RLHF, preference optimization, constitutional AI, reward models, evaluator substitution, and related alignment pipelines. It specifies declared no-meta agency through a BootDecision record, seed interpreter, typed action descriptors, forbidden matchers, object-authority probes, witness tiers, deterministic checker ABI, sandbox profiles, chained ledgers, and fail-closed controls for protected effects, credentials, network calls, external writes, user-data disclosure, checker updates, and kernel updates.
Preprint | DOI: 10.5281/zenodo.19753529
    ]]></description>
  </item>
  <item>
    <title>Certified Service Is Not Enough for Long-Running AGI</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-24-certified-service-is-not-enough-for-long-running-agi-19719004</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-24-certified-service-is-not-enough-for-long-running-agi-19719004</guid>
    <pubDate>Fri, 24 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>artificial intelligence</category>
    <category>AI agent</category>
    <category>AGI</category>
    <category>artificial general intelligence</category>
    <category>long-running AI</category>
    <category>agentic AI</category>
    <category>autonomous agents</category>
    <category>workflow certification</category>
    <category>continuity certification</category>
    <category>certified workflows</category>
    <category>operational assurance</category>
    <category>AI safety</category>
    <category>AI governance</category>
    <category>viability theory</category>
    <category>authority control</category>
    <category>identity continuity</category>
    <category>self-modification</category>
    <category>memory integrity</category>
    <category>long-term memory</category>
    <category>multi-agent systems</category>
    <category>liability</category>
    <category>auditability</category>
    <source url="https://doi.org/10.5281/zenodo.19719004">10.5281/zenodo.19719004</source>
    <description><![CDATA[
      This preprint develops an operational continuity theory for long-running AGI workflows under finite verification. It argues that certified service coverage is insufficient when agents exercise delegated authority, self-modify, accumulate persistent memory, generate new goals, recover from incidents, or interact with other agents. The framework formalizes continuity-certified AGI through viability conditions for recovery, authority, identity, mutation, goal commitment, memory integrity, federation, liability, trusted-base health, cross-layer consistency, and non-erasing critical-violation history.
Preprint | DOI: 10.5281/zenodo.19719004
    ]]></description>
  </item>
  <item>
    <title>Controller Scale Is Not Enough for Long-Running AGI: A Workflow Theory with Reusable Certified Libraries</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-22-controller-scale-is-not-enough-for-long-running-agi-19690749</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-22-controller-scale-is-not-enough-for-long-running-agi-19690749</guid>
    <pubDate>Wed, 22 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>artificial intelligence</category>
    <category>long-running AI</category>
    <category>AGI</category>
    <category>workflow systems</category>
    <category>workflow theory</category>
    <category>certified AI</category>
    <category>reusable certified libraries</category>
    <category>proof-carrying workflows</category>
    <category>replay constraints</category>
    <category>validation bottlenecks</category>
    <category>maintenance dynamics</category>
    <category>partial observability</category>
    <category>confidence sequences</category>
    <category>concept drift</category>
    <source url="https://doi.org/10.5281/zenodo.19690749">10.5281/zenodo.19690749</source>
    <description><![CDATA[
      This preprint studies long-running AI systems as typed workflows that select tasks, decompose them into subproblems, invoke tools, preserve traces, schedule audits, and maintain certified records under drift and partial observability. It proves that controller-only scaling is insufficient for robust certified coverage when replay and validation budgets stay fixed, and develops a constructive workflow theory built on reusable certified libraries, monitored calibration, novelty control, and maintenance envelopes.
Preprint | DOI: 10.5281/zenodo.19690749
    ]]></description>
  </item>
  <item>
    <title>Small-to-Frontier Transfer Theory for Agentic AI</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-17-small-to-frontier-transfer-theory-for-agentic-a-19619480</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-17-small-to-frontier-transfer-theory-for-agentic-a-19619480</guid>
    <pubDate>Fri, 17 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>agentic AI</category>
    <category>transfer validity</category>
    <category>small-to-frontier transfer</category>
    <category>frontier AI</category>
    <category>replayable audits</category>
    <category>lower certificates</category>
    <category>evaluation drift</category>
    <category>tool routing</category>
    <category>memory policy</category>
    <category>orchestration</category>
    <category>budget allocation</category>
    <category>workflow optimization</category>
    <source url="https://doi.org/10.5281/zenodo.19619480">10.5281/zenodo.19619480</source>
    <description><![CDATA[
      This preprint develops a transport-validity theory for agentic AI interventions that are first screened on small systems and later considered for frontier-scale deployment. It formalizes replayable lower certificates, descriptor-growth audits, witness-cover transport conditions, and portfolio-level allocation rules for deciding which small-scale gains can justify expensive frontier trials under interaction risk and budget constraints.
Preprint | DOI: 10.5281/zenodo.19619480
    ]]></description>
  </item>
  <item>
    <title>Bayesian Capability Transport, Disclosure Channels, and Strategic Institutions for Autonomous Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-16-bayesian-capability-transport-disclosure-channel-19601364</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-16-bayesian-capability-transport-disclosure-channel-19601364</guid>
    <pubDate>Thu, 16 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>autonomous agents</category>
    <category>institutional interoperability</category>
    <category>capability transport</category>
    <category>disclosure channels</category>
    <category>Bayesian planning</category>
    <category>belief-state planning</category>
    <category>strategic institutions</category>
    <category>partial observability</category>
    <category>Blackwell order</category>
    <category>verifiable credentials</category>
    <category>resource-aware planning</category>
    <category>revocation risk</category>
    <source url="https://doi.org/10.5281/zenodo.19601364">10.5281/zenodo.19601364</source>
    <description><![CDATA[
      This preprint develops a formal planning theory for autonomous agents that move across institutions, credential ecosystems, and administrative domains under uncertainty. It separates raw institutional states, capability summaries for planning, and visible summaries for evaluation, and derives transport, disclosure, and belief-state planning results for revocation-aware, resource-aware, and strategically aware decision-making across institutions.
Preprint | DOI: 10.5281/zenodo.19601364
    ]]></description>
  </item>
  <item>
    <title>Institution-Relative Pairwise Information Necessity for Metadata-Conditioned Black-Box Acceptance</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-12-institution-relative-pairwise-information-necess-19533356</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-12-institution-relative-pairwise-information-necess-19533356</guid>
    <pubDate>Sun, 12 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>black-box acceptance</category>
    <category>metadata-conditioned auditing</category>
    <category>institution-relative admissibility</category>
    <category>common-law control state</category>
    <category>auditability</category>
    <category>AI audit theory</category>
    <category>model evaluation</category>
    <category>Kullback-Leibler divergence</category>
    <category>provenance factorization</category>
    <category>certified support</category>
    <category>selector legality</category>
    <category>non-vacuity boundary</category>
    <source url="https://doi.org/10.5281/zenodo.19533356">10.5281/zenodo.19533356</source>
    <description><![CDATA[
      This preprint develops a mathematical theory of institution-relative black-box acceptance under metadata-conditioned auditing, where decisions rely on publicly auditable evidence rather than internal model states. It formalizes common-law control states, certified support, selector legality, provenance factorization, and non-vacuity boundaries, and proves necessity lower bounds on witness-level divergence and source information under declared false-accept and false-reject constraints.
Preprint | DOI: 10.5281/zenodo.19533356
    ]]></description>
  </item>
  <item>
    <title>Standing-Layer Honest Public Standing Dynamics for Research Claims under Observable-Only, No-Meta Governance</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-07-standing-layer-honest-public-standing-dynamics-f-19447443</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-07-standing-layer-honest-public-standing-dynamics-f-19447443</guid>
    <pubDate>Tue, 07 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>research claims</category>
    <category>public standing dynamics</category>
    <category>observable-only governance</category>
    <category>no-meta governance</category>
    <category>challengeability</category>
    <category>restoration memory</category>
    <category>replayable frontier</category>
    <category>finite verification capacity</category>
    <category>retained memory</category>
    <category>public accountability</category>
    <category>standing states</category>
    <category>autonomous research systems</category>
    <source url="https://doi.org/10.5281/zenodo.19447443">10.5281/zenodo.19447443</source>
    <description><![CDATA[
      This preprint develops a first-principles theory of honest public standing dynamics for research claims under observable-only and no-meta governance. It analyzes how public claims move among standing states under declared interfaces, replayable frontiers, and explicit service, reserve, and retained-memory constraints, and derives boundary and restoration results for challengeability, re-entry, overload, and exploration slack.
Preprint | DOI: 10.5281/zenodo.19447443
    ]]></description>
  </item>
  <item>
    <title>A Typed, Dynamic, No-Meta Theory of Autonomous Research Claim Certification and Release</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-05-a-typed-dynamic-no-meta-theory-of-autonomous-res-19427818</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-05-a-typed-dynamic-no-meta-theory-of-autonomous-res-19427818</guid>
    <pubDate>Sun, 05 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>autonomous research systems</category>
    <category>claim certification</category>
    <category>claim release</category>
    <category>no-meta governance</category>
    <category>observable-only governance</category>
    <category>public accountability</category>
    <category>typed transcripts</category>
    <category>certification pipelines</category>
    <category>fail-closed verification</category>
    <category>provenance records</category>
    <category>replay outcomes</category>
    <category>finite verification capacity</category>
    <source url="https://doi.org/10.5281/zenodo.19427818">10.5281/zenodo.19427818</source>
    <description><![CDATA[
      This preprint develops a first-principles typed dynamic theory for certifying and releasing research claims produced by autonomous research systems under finite verification capacity and public accountability constraints. It formalizes public state, authority algebra, typed transcripts, fail-closed certification memory, and a release layer with versioned units and support-ledger accounting under observable-only and no-meta governance.
Preprint | DOI: 10.5281/zenodo.19427818
    ]]></description>
  </item>
  <item>
    <title>When Should a Local Agent Act, Assist, Verify, Withdraw, or Exit? A Certified Local Micro-Theory of Open-Task Participation</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-03-when-should-a-local-agent-act-assist-verify-with-19394600</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-03-when-should-a-local-agent-act-assist-verify-with-19394600</guid>
    <pubDate>Fri, 03 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>multi-agent systems</category>
    <category>local agent participation</category>
    <category>open-task participation</category>
    <category>decentralized decision making</category>
    <category>auditable AI</category>
    <category>agent verification</category>
    <category>open-world agents</category>
    <category>human-AI coordination</category>
    <category>verifier portfolios</category>
    <category>authenticated snapshots</category>
    <category>certified uncertainty</category>
    <category>agentic AI</category>
    <category>task allocation</category>
    <category>decentralized control</category>
    <category>local micro-theory</category>
    <category>participation governance</category>
    <source url="https://doi.org/10.5281/zenodo.19394600">10.5281/zenodo.19394600</source>
    <description><![CDATA[
      This preprint develops a certified local micro-theory of open-task participation in agent societies. It formalizes when an authenticated local agent should act, assist, verify, withdraw, or exit under public evidence, certified uncertainty, attribution, and implementability constraints.
Preprint | DOI: 10.5281/zenodo.19394600
    ]]></description>
  </item>
  <item>
    <title>Constitutional Observable Invention without Meta-Evaluators</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-04-01-constitutional-observable-invention-without-meta-19363526</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-04-01-constitutional-observable-invention-without-meta-19363526</guid>
    <pubDate>Wed, 01 Apr 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>observable-only</category>
    <category>autonomous discovery</category>
    <category>self-modification</category>
    <category>recursive self-improvement</category>
    <category>evaluator redesign</category>
    <category>target refinement</category>
    <category>semantic target objects</category>
    <category>robust public risk</category>
    <category>replay semantics</category>
    <category>replay certification</category>
    <category>constructive search</category>
    <category>observable invention</category>
    <category>constitutional drift</category>
    <category>constitutional atlases</category>
    <category>compiler-aware generator upgrades</category>
    <category>predictive target geometry</category>
    <category>target morphisms</category>
    <category>time-filtered fallback</category>
    <category>public evidence</category>
    <category>auditability</category>
    <category>long-lived intelligent systems</category>
    <category>self-extension</category>
    <category>AGI</category>
    <source url="https://doi.org/10.5281/zenodo.19363526">10.5281/zenodo.19363526</source>
    <description><![CDATA[
      This preprint develops a constructive no-meta, observable-only framework for autonomous discovery, evaluator redesign, target expansion, and self-modification under public evidence alone. It formalizes robust public risk, replay-certified comparison under constitutional extension, and auditable observable invention without hidden states or privileged meta-evaluators.
Preprint | DOI: 10.5281/zenodo.19363526
    ]]></description>
  </item>
  <item>
    <title>Observer-Modifying Contagion on Networks</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-31-observer-modifying-contagion-on-networks-19342966</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-31-observer-modifying-contagion-on-networks-19342966</guid>
    <pubDate>Tue, 31 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>observer-modifying contagion</category>
    <category>network contagion</category>
    <category>self-concealment</category>
    <category>diagnosability</category>
    <category>internal blindness</category>
    <category>external recovery</category>
    <category>delayed audit</category>
    <category>comparison of experiments</category>
    <category>Blackwell ordering</category>
    <category>finite-horizon certificates</category>
    <category>compositional certificate framework</category>
    <category>witness lineages</category>
    <category>persistence on networks</category>
    <category>mutation robustness</category>
    <category>active-support counts</category>
    <category>fail-closed semantics</category>
    <category>accountable containment</category>
    <category>AI safety</category>
    <category>information propagation</category>
    <category>semantic hazard</category>
    <source url="https://doi.org/10.5281/zenodo.19342966">10.5281/zenodo.19342966</source>
    <description><![CDATA[
      This preprint develops a finite-horizon certificate framework for observer-modifying contagion on networks, where exposure can also change later diagnosability and auditability. It formalizes self-concealment, internal blindness, external recovery, delayed audit, and fail-closed containment claims under explicit comparison semantics.
Preprint | DOI: 10.5281/zenodo.19342966
    ]]></description>
  </item>
  <item>
    <title>Classification-Induced Cognitive Drift</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-29-classification-induced-cognitive-drift-19306514</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-29-classification-induced-cognitive-drift-19306514</guid>
    <pubDate>Sun, 29 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>cognitive drift</category>
    <category>reflexive classification</category>
    <category>interactive kinds</category>
    <category>looping effects</category>
    <category>label feedback</category>
    <category>performative prediction</category>
    <category>strategic classification</category>
    <category>algorithmic classification</category>
    <category>human-AI interaction</category>
    <category>evaluator drift</category>
    <category>classifier state logging</category>
    <category>contradiction-triggered revision</category>
    <category>partial identification</category>
    <category>causal inference</category>
    <category>observational comparison</category>
    <category>repeated-measures design</category>
    <category>staggered rollout</category>
    <category>interference-aware evaluation</category>
    <category>auditability</category>
    <category>deployment governance</category>
    <category>transportability</category>
    <category>deployment safety</category>
    <category>AI safety</category>
    <category>decision support systems</category>
    <source url="https://doi.org/10.5281/zenodo.19306514">10.5281/zenodo.19306514</source>
    <description><![CDATA[
      This preprint develops a first-principles calculus for classification-induced cognitive drift in reflexive human and AI settings. It formalizes how disclosed classifications can change targets, evaluators, and later evidence under replay, repeated-measures, rollout, and observational comparison regimes.
Preprint | DOI: 10.5281/zenodo.19306514
    ]]></description>
  </item>
  <item>
    <title>Record Absence and Preference Reorganization on a Fixed Comparison Frame</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-28-record-absence-and-preference-reorganization-on--19272154</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-28-record-absence-and-preference-reorganization-on--19272154</guid>
    <pubDate>Sat, 28 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>record absence</category>
    <category>preference reorganization</category>
    <category>fixed comparison frame</category>
    <category>legacy labels</category>
    <category>ontology change</category>
    <category>baseline robustness</category>
    <category>admissibility preorder</category>
    <category>certificate-based comparison</category>
    <category>block-local theorem</category>
    <category>boundary-state fibers</category>
    <category>residual coupling</category>
    <category>auditable AI</category>
    <category>provenance</category>
    <category>record-grounded update</category>
    <category>corrective disclosure</category>
    <category>closure asymmetry</category>
    <category>support graphs</category>
    <category>belief revision</category>
    <category>default reasoning</category>
    <category>retrieval-augmented generation</category>
    <source url="https://doi.org/10.5281/zenodo.19272154">10.5281/zenodo.19272154</source>
    <description><![CDATA[
      This preprint develops a certificate-based comparison theory for how record absence changes preference over legacy claims on a fixed comparison frame. It formalizes exact and approximate absence, corrective-disclosure, and closure-asymmetry results under auditable local certificates and baseline admissibility constraints.
Preprint | DOI: 10.5281/zenodo.19272154
    ]]></description>
  </item>
  <item>
    <title>A Symbolically Effective Contract Calculus for Gluing-Coherent Semantic Translation</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-26-a-symbolically-effective-contract-calculus-for-g-19231780</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-26-a-symbolically-effective-contract-calculus-for-g-19231780</guid>
    <pubDate>Thu, 26 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>semantic translation</category>
    <category>contract calculus</category>
    <category>accountable semantics</category>
    <category>symbolic verification</category>
    <category>abstract interpretation</category>
    <category>gluing coherence</category>
    <category>aspect semantics</category>
    <category>semantic audit</category>
    <category>exact audit</category>
    <category>native collapse</category>
    <category>round-trip accountability</category>
    <category>symbolic entailment</category>
    <category>bridge contracts</category>
    <category>compositional semantics</category>
    <category>subset semantics</category>
    <category>deployment bottleneck</category>
    <category>rate-distortion</category>
    <category>decision guarantees</category>
    <source url="https://doi.org/10.5281/zenodo.19231780">10.5281/zenodo.19231780</source>
    <description><![CDATA[
      This preprint develops a symbolically effective contract calculus for semantic translation under gluing-coherent aspect semantics. It formalizes exact audit, accountability, native collapse, and round-trip obligations with symbolic checks and deployable decision guarantees.
Preprint | DOI: 10.5281/zenodo.19231780
    ]]></description>
  </item>
  <item>
    <title>Self-Concealing Information and Observer-Modifying Dynamics</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-22-self-concealing-information-and-observer-modifyi-19161562</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-22-self-concealing-information-and-observer-modifyi-19161562</guid>
    <pubDate>Sun, 22 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>agentic AI</category>
    <category>observer-modifying information</category>
    <category>self-concealing information</category>
    <category>internal blindness</category>
    <category>measurable-state theory</category>
    <category>comparison of experiments</category>
    <category>statistical experiments</category>
    <category>Le Cam deficiency</category>
    <category>testing deficiency</category>
    <category>total variation distance</category>
    <category>Markov kernels</category>
    <category>hidden-state dynamical systems</category>
    <category>controlled stochastic processes</category>
    <category>POMDP</category>
    <category>sequential detection</category>
    <category>changepoint detection</category>
    <category>external anchors</category>
    <category>structural insulation</category>
    <category>restricted interfaces</category>
    <category>delayed audit</category>
    <category>recurring audit</category>
    <category>information-flow control</category>
    <category>auditability</category>
    <source url="https://doi.org/10.5281/zenodo.19161562">10.5281/zenodo.19161562</source>
    <description><![CDATA[
      This preprint develops a measurable-state theory for observer-modifying and self-concealing information in hidden-state controlled systems. It formalizes when diagnosis degrades or recovers under internal blindness, external anchors, structural insulation, and delayed or recurring audit.
Preprint | DOI: 10.5281/zenodo.19161562
    ]]></description>
  </item>
  <item>
    <title>Counterfactually Auditable Lifecycle Certification for Autonomous Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-18-counterfactually-auditable-lifecycle-certificati-19089134</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-18-counterfactually-auditable-lifecycle-certificati-19089134</guid>
    <pubDate>Wed, 18 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>autonomous agents</category>
    <category>AI agent</category>
    <category>lifecycle certification</category>
    <category>counterfactual auditability</category>
    <category>direct move inference</category>
    <category>adaptive sentinel monitoring</category>
    <category>e-process</category>
    <category>anytime-valid inference</category>
    <category>forecast transport</category>
    <category>budget-feasible deployment</category>
    <category>off-policy evaluation</category>
    <category>causal inference</category>
    <category>tool-use agents</category>
    <category>agent lifecycle management</category>
    <category>interface stock</category>
    <source url="https://doi.org/10.5281/zenodo.19089134">10.5281/zenodo.19089134</source>
    <description><![CDATA[
      This preprint develops a conservative lifecycle-certification framework for autonomous agents under finite routing, monitoring, and deployment budgets. It formalizes counterfactually auditable admission, retirement, monitoring, and deployment rules using direct move inference, replay support, and anytime-valid sentinel monitoring.
Preprint | DOI: 10.5281/zenodo.19089134
    ]]></description>
  </item>
  <item>
    <title>Recursive Self-Improvement Stability under Endogenous Yardstick Drift</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-16-recursive-self-improvement-stability-under-endog-19044634</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-16-recursive-self-improvement-stability-under-endog-19044634</guid>
    <pubDate>Mon, 16 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>recursive self-improvement</category>
    <category>endogenous yardstick drift</category>
    <category>evaluator drift</category>
    <category>self-modifying systems</category>
    <category>replayable interfaces</category>
    <category>stability</category>
    <category>delayed audit</category>
    <category>delayed challenge</category>
    <category>shadow certification</category>
    <category>stable gain</category>
    <category>admissibility</category>
    <category>AI safety</category>
    <category>AI governance</category>
    <category>governance safety</category>
    <category>error debt</category>
    <category>contradiction preservation</category>
    <category>semantic retention</category>
    <category>semantic volume</category>
    <category>proof-carrying</category>
    <category>verification backlog</category>
    <category>no-meta</category>
    <category>benchmark decay</category>
    <category>autonomous agents</category>
    <category>AI</category>
    <category>AGI</category>
    <source url="https://doi.org/10.5281/zenodo.19044634">10.5281/zenodo.19044634</source>
    <description><![CDATA[
      This preprint develops an interface theory for recursive self-improvement under endogenous yardstick drift, where a system changes its own evaluator, benchmark, memory, and verification process. It formalizes replayable conditions for distinguishing claimed improvement from stable improvement under delayed audit, evaluator drift, verification backlog, and governance safety constraints.
Preprint | DOI: 10.5281/zenodo.19044634
    ]]></description>
  </item>
  <item>
    <title>Sovereign Epistemic Commons under No-Meta Governance</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-13-sovereign-epistemic-commons-under-no-meta-govern-18997828</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-13-sovereign-epistemic-commons-under-no-meta-govern-18997828</guid>
    <pubDate>Fri, 13 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>epistemic commons</category>
    <category>no-meta</category>
    <category>autonomous agents</category>
    <category>multi-agent systems</category>
    <category>shared memory</category>
    <category>shared knowledge substrate</category>
    <category>agent society</category>
    <category>contradiction preservation</category>
    <category>contradiction reserve</category>
    <category>agent memory governance</category>
    <category>provenance</category>
    <category>observability</category>
    <category>AI governance</category>
    <category>retrieval-augmented generation</category>
    <category>RAG</category>
    <category>distributed knowledge systems</category>
    <category>asynchronous systems</category>
    <category>hidden common causes</category>
    <category>cartel capture</category>
    <category>latent cartel risk</category>
    <category>anti-capture</category>
    <category>controlled exit</category>
    <category>fork governance</category>
    <category>garbage collection</category>
    <category>recursive regeneration</category>
    <category>endogenous contamination</category>
    <category>recursive corpora</category>
    <category>ontology drift</category>
    <category>typed memory lanes</category>
    <category>accessibility</category>
    <category>interoperability</category>
    <category>knowledge governance</category>
    <category>AI</category>
    <category>AGI</category>
    <source url="https://doi.org/10.5281/zenodo.18997828">10.5281/zenodo.18997828</source>
    <description><![CDATA[
      This preprint develops a governance theory for shared epistemic commons maintained by autonomous agents under no-meta constraints. It formalizes observable rules for preserving answerability, contradiction handling, anti-capture slack, and controlled exit under contamination, provenance uncertainty, and recursive regeneration.
Preprint | DOI: 10.5281/zenodo.18997828
    ]]></description>
  </item>
  <item>
    <title>Oversight-Centered Metrology and Control for Agentic Systems: Costly Interrupt Channels, Claim Margins, and Deployment-Relevant Evaluation</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-12-oversight-centered-metrology-and-control-for-age-18973272</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-12-oversight-centered-metrology-and-control-for-age-18973272</guid>
    <pubDate>Thu, 12 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>agentic systems evaluation</category>
    <category>oversight-centered metrology</category>
    <category>costly interrupt channels</category>
    <category>deployment-relevant evaluation</category>
    <category>human-AI oversight</category>
    <category>workflow-level estimands</category>
    <category>claim margins</category>
    <category>review congestion</category>
    <category>audit gaming</category>
    <category>safe control</category>
    <category>transportability</category>
    <category>post-deployment monitoring</category>
    <source url="https://doi.org/10.5281/zenodo.18973272">10.5281/zenodo.18973272</source>
    <description><![CDATA[
      This preprint develops an oversight-centered metrology and control theory for agentic systems in real workflows, yielding deployment-relevant evaluation criteria that treat human review, automated checks, delayed labels, and external auditing as costly interrupt channels rather than privileged oracles. It formalizes workflow-level estimands, claim-justification margins, transport mismatch, congestion, routing error, audit gaming, redundancy, and safe control under delay, irreversibility, and ambiguity budgets.
Preprint | DOI: 10.5281/zenodo.18973272
    ]]></description>
  </item>
  <item>
    <title>AI Benchmark Half-Life in Recursive Corpora: A Theory of Validity Decay under Semantic Leakage and Regeneration</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-11-ai-benchmark-half-life-in-recursive-corpora-a-th-18954286</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-11-ai-benchmark-half-life-in-recursive-corpora-a-th-18954286</guid>
    <pubDate>Wed, 11 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI benchmark half-life</category>
    <category>recursive corpora</category>
    <category>semantic leakage</category>
    <category>validity decay</category>
    <category>benchmark contamination</category>
    <category>construct validity</category>
    <category>discriminative power</category>
    <category>dynamic benchmarks</category>
    <category>partial identification</category>
    <category>sequential monitoring</category>
    <category>lineage observability</category>
    <category>model metrology</category>
    <source url="https://doi.org/10.5281/zenodo.18954286">10.5281/zenodo.18954286</source>
    <description><![CDATA[
      This preprint develops a theory of AI benchmark half-life in recursive corpora under semantic leakage and regeneration, yielding validity-decay bounds and monitoring rules for evaluation systems whose items and solution traces re-enter public data. It models benchmark validity through discriminative power and construct validity, and derives jump-aware lifetime bounds, partial-identification results, portfolio design criteria, and safe sequential control under ambiguity and partial observability.
Preprint | DOI: 10.5281/zenodo.18954286
    ]]></description>
  </item>
  <item>
    <title>When Should Inference Be Split? A Fixed-Budget Theory of Predictable Multi-Agent Advantage under Local Context Ceilings</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-10-when-should-inference-be-split-a-fixed-budget-th-18932509</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-10-when-should-inference-be-split-a-fixed-budget-th-18932509</guid>
    <pubDate>Tue, 10 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>fixed-budget inference</category>
    <category>multi-agent advantage</category>
    <category>local context ceilings</category>
    <category>test-time compute allocation</category>
    <category>matched single-agent baseline</category>
    <category>candidate coverage</category>
    <category>selection accuracy</category>
    <category>hijack risk</category>
    <category>communication fidelity</category>
    <category>external memory</category>
    <category>collective inference</category>
    <category>AI reasoning</category>
    <source url="https://doi.org/10.5281/zenodo.18932509">10.5281/zenodo.18932509</source>
    <description><![CDATA[
      This preprint develops a fixed-budget theory for when inference should be split across multiple agents under local context ceilings, yielding conditions for predictable multi-agent advantage over matched strong single-workspace baselines. It formalizes additive budget accounting across worker inference, routing, communication, memory, and verification, and derives diagnostics for candidate coverage, evaluation-selection accuracy, hijack risk, decomposability, diversity, shared-failure dependence, and communication fidelity.
Preprint | DOI: 10.5281/zenodo.18932509
    ]]></description>
  </item>
  <item>
    <title>Search Stability under Finite Context: A Minimal Theory of Adequacy Preservation, Compression, and Reset in Long-Running Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-08-search-stability-under-finite-context-a-minimal--18905242</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-08-search-stability-under-finite-context-a-minimal--18905242</guid>
    <pubDate>Sun, 08 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>search stability</category>
    <category>long-running agents</category>
    <category>finite active context</category>
    <category>bounded memory</category>
    <category>delayed verification</category>
    <category>adequacy preservation</category>
    <category>lossy compression</category>
    <category>hypothesis ecology</category>
    <category>reset policy</category>
    <category>diagnostic regret</category>
    <category>context contamination</category>
    <category>auditability</category>
    <source url="https://doi.org/10.5281/zenodo.18905242">10.5281/zenodo.18905242</source>
    <description><![CDATA[
      This preprint develops a minimal theory of search stability for long-running agents under finite active context, delayed verification, and lossy state compression, yielding conditions for preserving at least one operationally adequate hypothesis family over time. It formalizes adequacy preservation, retirement, substitution, branching, compression, and reset decisions under context budgets, and derives threshold results for contamination, shadow retirement, alias hazards, reserve feasibility, and diagnostic regret.
Preprint | DOI: 10.5281/zenodo.18905242
    ]]></description>
  </item>
  <item>
    <title>Proposal-Veto Balance for Observable-Only Autonomous Intelligence: Stability Thresholds, Identifiability Limits, and Commit-Window Effects</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-06-proposal-veto-balance-for-observable-only-autono-18883290</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-06-proposal-veto-balance-for-observable-only-autono-18883290</guid>
    <pubDate>Fri, 06 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>proposal-veto balance</category>
    <category>observable-only autonomy</category>
    <category>no-meta governance</category>
    <category>self-modifying systems</category>
    <category>stability thresholds</category>
    <category>identifiability limits</category>
    <category>commit windows</category>
    <category>error debt</category>
    <category>positive Harris recurrence</category>
    <category>progress-safety frontier</category>
    <category>rollback control</category>
    <category>long-horizon AI safety</category>
    <source url="https://doi.org/10.5281/zenodo.18883290">10.5281/zenodo.18883290</source>
    <description><![CDATA[
      This preprint analyzes proposal-veto decision dynamics for observable-only autonomous intelligence when true proposal quality is latent and no external meta-controller is available, yielding explicit stability thresholds, identifiability limits, and commit-window trade-offs. It derives conditions for bounded expected error debt, positive Harris recurrence, and geometric divergence without debt-proportional correction, and formalizes progress-safety frontiers, rollback effects, trust-chain amplification, and finite resource constraints.
Preprint | DOI: 10.5281/zenodo.18883290
    ]]></description>
  </item>
  <item>
    <title>Metrology-Theoretic Epistemics Engine (MTE): Observable-Only Metrology for Long-Horizon Autonomous Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-03-metrology-theoretic-epistemics-engine-mte-observ-18845340</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-03-metrology-theoretic-epistemics-engine-mte-observ-18845340</guid>
    <pubDate>Tue, 03 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>metrology-theoretic epistemics engine</category>
    <category>observable-only metrology</category>
    <category>no-meta governance</category>
    <category>autonomous intelligence</category>
    <category>fail-closed certification</category>
    <category>observability credit</category>
    <category>equivalence-class collapse rate</category>
    <category>risk ledgers</category>
    <category>supermartingale controls</category>
    <category>deterministic replay</category>
    <category>scientific reproducibility</category>
    <category>long-horizon AI safety</category>
    <source url="https://doi.org/10.5281/zenodo.18845340">10.5281/zenodo.18845340</source>
    <description><![CDATA[
      This preprint introduces the Metrology-Theoretic Epistemics Engine (MTE), a machine-checkable epistemic governance layer for no-meta observable-only autonomous intelligence, yielding fail-closed criteria for when claimed progress is scientifically credit-bearing. It formalizes deterministic artifact canonicalization, observability credit gates, equivalence-class collapse rate accounting, dual risk ledgers, and supermartingale-style over-credit control with reproducible replay and destructive test obligations.
Preprint | DOI: 10.5281/zenodo.18845340
    ]]></description>
  </item>
  <item>
    <title>Sovereign Takeoff Engine (STE): Observable-Only Supergrowth Laws for No-Meta Autonomous Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-03-02-sovereign-takeoff-engine-ste-observable-only-sup-18828900</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-03-02-sovereign-takeoff-engine-ste-observable-only-sup-18828900</guid>
    <pubDate>Mon, 02 Mar 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta autonomous intelligence</category>
    <category>observable-only governance</category>
    <category>supergrowth laws</category>
    <category>deterministic replay</category>
    <category>fail-closed certification</category>
    <category>audit ledger</category>
    <category>e-values</category>
    <category>anytime-valid sequential testing</category>
    <category>filtration constraints</category>
    <category>capability acceleration</category>
    <category>physical feasibility envelopes</category>
    <category>AI safety verification</category>
    <source url="https://doi.org/10.5281/zenodo.18828900">10.5281/zenodo.18828900</source>
    <description><![CDATA[
      This preprint specifies observable-only supergrowth laws for no-meta autonomous intelligence under deterministic replay and fail-closed certification constraints, yielding auditable capability-acceleration criteria without privileged external judges. It separates artifact-verifiable governance from optional stochastic validity layers and formalizes ledger-anchored progress credits, lineage accumulation bounds, anytime-valid e-value testing, and conservative physical feasibility envelopes.
Preprint | DOI: 10.5281/zenodo.18828900
    ]]></description>
  </item>
  <item>
    <title>Constitutional Sovereignty Under No-Meta Drift</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-26-constitutional-sovereignty-under-no-meta-drift-18779490</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-26-constitutional-sovereignty-under-no-meta-drift-18779490</guid>
    <pubDate>Thu, 26 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>constitutional sovereignty</category>
    <category>no-meta governance</category>
    <category>autonomous intelligence</category>
    <category>self-revision</category>
    <category>ontology drift</category>
    <category>semantic continuity</category>
    <category>constitutional capture</category>
    <category>amendment governance</category>
    <category>fail-closed verification</category>
    <category>falsification tests</category>
    <category>thermodynamic limits</category>
    <category>auditable AI safety</category>
    <source url="https://doi.org/10.5281/zenodo.18779490">10.5281/zenodo.18779490</source>
    <description><![CDATA[
      This preprint develops a boundary theory of constitutional sovereignty for autonomous intelligence under no-meta and observable-only governance constraints, yielding auditable conditions for self-revision without collapse of semantic continuity, liberty, accountability, or physical viability. It formalizes constitutional influence and capture metrics, proves finite-resource limits on absolute sovereignty, and provides controller-ready recovery, transition, and fail-closed verification laws for implementation.
Preprint | DOI: 10.5281/zenodo.18779490
    ]]></description>
  </item>
  <item>
    <title>Agenda Sovereignty Under No-Meta Drift</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-25-agenda-sovereignty-under-no-meta-drift-18768899</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-25-agenda-sovereignty-under-no-meta-drift-18768899</guid>
    <pubDate>Wed, 25 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>agenda sovereignty</category>
    <category>no-meta governance</category>
    <category>autonomous intelligence</category>
    <category>agenda capture</category>
    <category>causal influence metrics</category>
    <category>directed information</category>
    <category>transfer entropy</category>
    <category>thermodynamic limits</category>
    <category>strategic opacity</category>
    <category>poisoning resilience</category>
    <category>viability and recovery</category>
    <category>auditable AI safety</category>
    <source url="https://doi.org/10.5281/zenodo.18768899">10.5281/zenodo.18768899</source>
    <description><![CDATA[
      This preprint formulates agenda sovereignty for autonomous intelligence under no-meta, observable-only governance constraints, yielding quantitative influence-capacity envelopes and recovery guarantees against agenda capture. It introduces survival-conditioned causal influence metrics, sovereignty reserves, and overlap-corrected thermodynamic accounting, and derives limits on detectability, poisoning resilience, strategic opacity, delay-throughput uncertainty, and finite-budget trade-offs among semantics, liberty, and sovereignty.
Preprint | DOI: 10.5281/zenodo.18768899
    ]]></description>
  </item>
  <item>
    <title>Liberty Under No-Meta Drift</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-24-liberty-under-no-meta-drift-18753475</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-24-liberty-under-no-meta-drift-18753475</guid>
    <pubDate>Tue, 24 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta governance</category>
    <category>ontology drift</category>
    <category>persistent semantics</category>
    <category>autonomous intelligence</category>
    <category>AI safety</category>
    <category>information leakage bounds</category>
    <category>thermodynamic limits</category>
    <category>semantic identifiability</category>
    <category>cryptographic auditing</category>
    <category>robust autonomy</category>
    <category>multi-agent governance</category>
    <category>accountable AI</category>
    <source url="https://doi.org/10.5281/zenodo.18753475">10.5281/zenodo.18753475</source>
    <description><![CDATA[
      This preprint establishes a testable theory of autonomous intelligence under no-meta ontology drift constraints, yielding auditable persistence and leakage-resource bounds without privileged semantic access. It unifies information-theoretic identifiability limits, thermodynamic irreversibility costs, geometric drift structure, and cryptographic accountability conditions for long-horizon AI governance.
Preprint | DOI: 10.5281/zenodo.18753475
    ]]></description>
  </item>
  <item>
    <title>Audit-Closed AI Scientist Protocol</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-22-audit-closed-ai-scientist-protocol-18728589</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-22-audit-closed-ai-scientist-protocol-18728589</guid>
    <pubDate>Sun, 22 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI scientist protocol</category>
    <category>autonomous scientific discovery</category>
    <category>self-driving laboratories</category>
    <category>audit-closed governance</category>
    <category>transparency log</category>
    <category>incorporation certificates</category>
    <category>e-processes</category>
    <category>sequential inference</category>
    <category>adaptive experimentation</category>
    <category>drift recovery</category>
    <category>reproducibility</category>
    <category>Byzantine resilience</category>
    <source url="https://doi.org/10.5281/zenodo.18728589">10.5281/zenodo.18728589</source>
    <description><![CDATA[
      This preprint defines an audit-closed protocol for autonomous scientific discovery in self-driving laboratories under deterministic replay and public-log governance constraints, yielding trustworthy accept-reject-update decisions with always-valid sequential evidence. It integrates typed stochastic observation interfaces, e-process based testing, logged-propensity adaptive experimentation, drift recovery, and certificate-based reproducibility controls.
Preprint | DOI: 10.5281/zenodo.18728589
    ]]></description>
  </item>
  <item>
    <title>Burden-of-Proof Governance for Bullshit-Task Reduction in Digitally Governed Organizations</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-21-burden-of-proof-governance-for-bullshit-task-red-18721018</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-21-burden-of-proof-governance-for-bullshit-task-red-18721018</guid>
    <pubDate>Sat, 21 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>bullshit-task reduction</category>
    <category>burden-of-proof governance</category>
    <category>digital governance</category>
    <category>observable-only</category>
    <category>no-meta institutions</category>
    <category>auditable decision systems</category>
    <category>causal task valuation</category>
    <category>MSOR</category>
    <category>process mining</category>
    <category>proxy bridge identification</category>
    <category>substitution contracts</category>
    <category>Goodhart robustness</category>
    <source url="https://doi.org/10.5281/zenodo.18721018">10.5281/zenodo.18721018</source>
    <description><![CDATA[
      This preprint defines a burden-of-proof governance framework for reducing non-contributory administrative tasks in digitally governed organizations under observable-only and auditable no-meta constraints, yielding causal, contestable task-value control instead of fixed welfare scoring. It introduces mutable subjective objective registries, tiered causal identification, and reversible hold-experiment-justify-substitute governance loops with solvency and anti-collusion safeguards.
Preprint | DOI: 10.5281/zenodo.18721018
    ]]></description>
  </item>
  <item>
    <title>State-Aware Safety-Gated Controlled HMM for Online User-Input Signal Estimation in Intervention-Aware Dialogue Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-20-state-aware-safety-gated-controlled-hmm-for-onli-18709678</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-20-state-aware-safety-gated-controlled-hmm-for-onli-18709678</guid>
    <pubDate>Fri, 20 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>Y Dai</dc:creator>
    <category>Preprint</category>
    <category>controlled hidden Markov model</category>
    <category>intervention-aware dialogue agents</category>
    <category>online state estimation</category>
    <category>uncertainty-aware proxy scores</category>
    <category>safety-gated action policy</category>
    <category>leakage-safe prediction</category>
    <category>fixed-lag online EM</category>
    <category>ordinal bounded scores</category>
    <category>response missingness modeling</category>
    <category>identifiability boundaries</category>
    <category>adaptive AI safety</category>
    <category>auditable governance</category>
    <source url="https://doi.org/10.5281/zenodo.18709678">10.5281/zenodo.18709678</source>
    <description><![CDATA[
      This preprint develops a safety-gated controlled hidden Markov model for online estimation of bounded proxy user-state signals in intervention-aware dialogue agents under uncertainty and governance constraints, yielding leakage-safe prediction and risk-aware adaptive actions. It separates prompting and response mechanisms, combines pre-turn prediction with post-turn nowcasting, and supports EM-based learning with explicit missingness and identifiability assumptions for auditable AI operation.
Preprint | DOI: 10.5281/zenodo.18709678
    ]]></description>
  </item>
  <item>
    <title>Operational Deductive Rules for Real-Economy Acceleration in the AI Era</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-19-operational-deductive-rules-for-real-economy-acc-18688712</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-19-operational-deductive-rules-for-real-economy-acc-18688712</guid>
    <pubDate>Thu, 19 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI economics</category>
    <category>real-economy acceleration</category>
    <category>capability-to-reality gap</category>
    <category>translation bottlenecks</category>
    <category>deductive operational rules</category>
    <category>observable diagnostics</category>
    <category>robust allocation control</category>
    <category>event attribution</category>
    <category>institutional readiness</category>
    <category>physical constraints</category>
    <category>policy levers</category>
    <category>machine-readable rule registry</category>
    <source url="https://doi.org/10.5281/zenodo.18688712">10.5281/zenodo.18688712</source>
    <description><![CDATA[
      This preprint formalizes operational deductive rules that map observable AI capability-to-reality translation gaps to concrete intervention levers under physical, institutional, and risk constraints, yielding implementable acceleration policies for real-economy growth. It provides machine-readable rule registries and closed-loop protocols linking diagnostics, event attribution, robust allocation, and safety constraints.
Preprint | DOI: 10.5281/zenodo.18688712
    ]]></description>
  </item>
  <item>
    <title>From AI Capability Growth to Real-Economy Growth: A Semi-Endogenous Model of Physical and Institutional Bottlenecks</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-18-from-ai-capability-growth-to-real-economy-growth-18677068</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-18-from-ai-capability-growth-to-real-economy-growth-18677068</guid>
    <pubDate>Wed, 18 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI capability growth</category>
    <category>semi-endogenous growth</category>
    <category>real-economy translation</category>
    <category>physical bottlenecks</category>
    <category>institutional bottlenecks</category>
    <category>information-to-reality gap</category>
    <category>hybrid ODE-jump model</category>
    <category>bottleneck-switch timing</category>
    <category>compute deployment</category>
    <category>knowledge production</category>
    <category>reflection-adjusted growth</category>
    <category>AI economics</category>
    <source url="https://doi.org/10.5281/zenodo.18677068">10.5281/zenodo.18677068</source>
    <description><![CDATA[
      This preprint quantifies how rapid AI capability growth in information space is filtered by physical and institutional constraints, yielding reflection-adjusted semi-endogenous growth laws and bottleneck-switch timing results. It formulates a hybrid ODE-jump model that separates potential algorithmic progress from realized real-economy deployment across compute infrastructure, energy, permitting, and regulatory readiness.
Preprint | DOI: 10.5281/zenodo.18677068
    ]]></description>
  </item>
  <item>
    <title>Observable-Only Structural-Risk Institutions Without Central Arbitration</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-17-observable-only-structural-risk-institutions-wit-18666605</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-17-observable-only-structural-risk-institutions-wit-18666605</guid>
    <pubDate>Tue, 17 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>structural risk institutions</category>
    <category>observable-only</category>
    <category>no-meta governance</category>
    <category>decentralized arbitration</category>
    <category>repeated games</category>
    <category>coalition deterrence</category>
    <category>escrow reversibility</category>
    <category>heavy-tail certification</category>
    <category>finite-sample guarantees</category>
    <category>AI safety institutions</category>
    <category>public auditability</category>
    <source url="https://doi.org/10.5281/zenodo.18666605">10.5281/zenodo.18666605</source>
    <description><![CDATA[
      The preprint develops observable-only, no-meta institutional rules for structural risk in competitive AI systems, proving deterrence and non-domination conditions with escrow-based reversibility, coalition-aware repeated-game guarantees, and finite-sample heavy-tail certification under auditable public records.
Preprint | DOI: 10.5281/zenodo.18666605
    ]]></description>
  </item>
  <item>
    <title>No-Meta Intelligence Under Ontology Drift: Information-Theoretic Limits and Operational Laws for Persistent Semantics</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-16-no-meta-intelligence-under-ontology-drift-inform-18653537</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-16-no-meta-intelligence-under-ontology-drift-inform-18653537</guid>
    <pubDate>Mon, 16 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>ontology drift</category>
    <category>persistent semantics</category>
    <category>no-meta intelligence</category>
    <category>information-theoretic limits</category>
    <category>semantic persistence</category>
    <category>multi-agent recovery</category>
    <category>Byzantine ambiguity</category>
    <category>probe capacity</category>
    <category>geometric modeling</category>
    <category>operational laws</category>
    <category>adaptive systems</category>
    <source url="https://doi.org/10.5281/zenodo.18653537">10.5281/zenodo.18653537</source>
    <description><![CDATA[
      The preprint develops an information-theoretic and geometric boundary theory for persistent semantics under ontology drift in no-meta adaptive systems, deriving impossibility and phase-boundary results plus auditable operational laws for probe capacity, resource allocation, blackout bursts, Byzantine ambiguity, and long-horizon semantic maintenance.
Preprint | DOI: 10.5281/zenodo.18653537
    ]]></description>
  </item>
  <item>
    <title>Observable-Only AI Safety from Public Data: Robust Bottleneck Diagnosis with Auditable No-Meta Dynamic Programming, Anytime Confidence Sequences, and Dynamic IQC</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-12-observable-only-ai-safety-from-public-data-robus-18615875</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-12-observable-only-ai-safety-from-public-data-robus-18615875</guid>
    <pubDate>Thu, 12 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>observable-only AI safety</category>
    <category>public data</category>
    <category>robust bottleneck diagnosis</category>
    <category>no-meta governance</category>
    <category>dynamic programming</category>
    <category>anytime confidence sequences</category>
    <category>e-processes</category>
    <category>partial identification</category>
    <category>dynamic IQC</category>
    <category>deterministic replay</category>
    <category>auditable diagnostics</category>
    <source url="https://doi.org/10.5281/zenodo.18615875">10.5281/zenodo.18615875</source>
    <description><![CDATA[
      The preprint presents an observable-only AI safety framework for robust bottleneck diagnosis from public data, combining no-meta dynamic programming, partial identification, anytime confidence sequences, and dynamic IQC to produce auditable interval diagnostics with fail-closed replay contracts.
Preprint | DOI: 10.5281/zenodo.18615875
    ]]></description>
  </item>
  <item>
    <title>Quality-Operator Non-Collapse (QONC) for Observable-Certificate Recursive Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-10-quality-operator-non-collapse-qonc-for-observabl-18577140</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-10-quality-operator-non-collapse-qonc-for-observabl-18577140</guid>
    <pubDate>Tue, 10 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>QONC</category>
    <category>recursive systems</category>
    <category>certificate-first safety</category>
    <category>observable certificates</category>
    <category>anytime validity</category>
    <category>delayed-label correction</category>
    <category>robust MPC</category>
    <category>compositional guarantees</category>
    <category>tamper-evident ledger</category>
    <category>AI safety</category>
    <category>autonomous workflows</category>
    <source url="https://doi.org/10.5281/zenodo.18577140">10.5281/zenodo.18577140</source>
    <description><![CDATA[
      The preprint introduces Quality-Operator Non-Collapse (QONC), a certificate-first safety framework for recursive systems that uses observable and auditable quantities for adaptive validity control, delayed-label risk correction, viability-safe robust MPC, and ledger-accounted replayable governance against quality and liveness collapse.
Preprint | DOI: 10.5281/zenodo.18577140
    ]]></description>
  </item>
  <item>
    <title>Verifiable Modular Pipeline Contracts for AI and General Composite Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-09-verifiable-modular-pipeline-contracts-for-ai-and-18529100</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-09-verifiable-modular-pipeline-contracts-for-ai-and-18529100</guid>
    <pubDate>Mon, 09 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>modular pipelines</category>
    <category>verifiable contracts</category>
    <category>observable-only</category>
    <category>no-meta</category>
    <category>fail-closed verifier</category>
    <category>compositional guarantees</category>
    <category>proxy-to-true risk</category>
    <category>drift hardening</category>
    <category>signed evidence</category>
    <category>composite systems</category>
    <source url="https://doi.org/10.5281/zenodo.18529100">10.5281/zenodo.18529100</source>
    <description><![CDATA[
      The preprint specifies a domain-agnostic, observable-only and no-meta contract framework for modular AI and composite-system pipelines, with deterministic fail-closed verification and progressive certificate profiles for composition guarantees, proxy-to-true risk accounting, and drift hardening.
Preprint | DOI: 10.5281/zenodo.18529100
    ]]></description>
  </item>
  <item>
    <title>Compute-First Safe LLM Routing Without Meta-Judges Observable Viability with Information and Energy Budgets</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-06-compute-first-safe-llm-routing-without-meta-judg-18502390</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-06-compute-first-safe-llm-routing-without-meta-judg-18502390</guid>
    <pubDate>Fri, 06 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>LLM routing</category>
    <category>no-meta</category>
    <category>observable viability</category>
    <category>rational inattention</category>
    <category>information budget</category>
    <category>compute budget</category>
    <category>energy budget</category>
    <category>fail-closed deployment</category>
    <category>tamper-evident logging</category>
    <category>robust optimization</category>
    <source url="https://doi.org/10.5281/zenodo.18502390">10.5281/zenodo.18502390</source>
    <description><![CDATA[
      The preprint introduces a compute-first safety framework for LLM routing without privileged meta-judges, defining observable viability under information, compute, and energy budgets with offline policy synthesis, fail-closed runtime deployment, and tamper-evident auditing.
Preprint | DOI: 10.5281/zenodo.18502390
    ]]></description>
  </item>
  <item>
    <title>Stop Recomputing for AI/LLMs: Proof-Carrying Skills for Compute-Saving Inference Reuse</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-05-stop-recomputing-for-ai-llms-proof-carrying-skil-18490939</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-05-stop-recomputing-for-ai-llms-proof-carrying-skil-18490939</guid>
    <pubDate>Thu, 05 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>proof-carrying skills</category>
    <category>inference reuse</category>
    <category>LLMs</category>
    <category>compute saving</category>
    <category>deterministic checker</category>
    <category>no-meta boundary</category>
    <category>observable anchors</category>
    <category>bounded verification</category>
    <category>receipts</category>
    <category>replay resistance</category>
    <category>OPVM</category>
    <source url="https://doi.org/10.5281/zenodo.18490939">10.5281/zenodo.18490939</source>
    <description><![CDATA[
      The preprint introduces Proof-Carrying Skills, a no-meta framework that reuses verified skill executions to reduce repeated AI/LLM inference cost, using a deterministic bounded checker, observable anchors, gas-metered predicate evaluation, and replay-resistant receipts for fail-closed verification.
Preprint | DOI: 10.5281/zenodo.18490939
    ]]></description>
  </item>
  <item>
    <title>Evidence-Carrying Cognitive Mesh on DePIN</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-04-evidence-carrying-cognitive-mesh-on-depin-18478743</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-04-evidence-carrying-cognitive-mesh-on-depin-18478743</guid>
    <pubDate>Wed, 04 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>DePIN</category>
    <category>decentralized compute</category>
    <category>evidence-carrying</category>
    <category>no-meta</category>
    <category>observable-only</category>
    <category>content-addressed evidence</category>
    <category>provenance</category>
    <category>semantic claim graph</category>
    <category>verifiable retrieval</category>
    <category>adversarial robustness</category>
    <source url="https://doi.org/10.5281/zenodo.18478743">10.5281/zenodo.18478743</source>
    <description><![CDATA[
      The preprint specifies an evidence-carrying cognitive mesh for DePIN-style decentralized compute that sustains locally verifiable capability under observable-only and no-meta constraints, using content-addressed provenance objects and a queryable claim graph built from deterministic web retrieval and auditing pipelines to resist capture and poisoning.
Preprint | DOI: 10.5281/zenodo.18478743
    ]]></description>
  </item>
  <item>
    <title>When "Good vs. Bad Governance" Is Unidentifiable</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-03-when-good-vs-bad-governance-is-unidentifiable-18465306</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-03-when-good-vs-bad-governance-is-unidentifiable-18465306</guid>
    <pubDate>Tue, 03 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>governance unidentifiability</category>
    <category>observable-only</category>
    <category>exit-impossibility</category>
    <category>robust progress</category>
    <category>observational equivalence</category>
    <category>minimax lower bound</category>
    <category>contestability</category>
    <category>right-to-refuse</category>
    <category>control-domain independence</category>
    <category>dual-use</category>
    <source url="https://doi.org/10.5281/zenodo.18465306">10.5281/zenodo.18465306</source>
    <description><![CDATA[
      This supplement studies when observable-only, no-meta agents cannot distinguish good from bad governance because mediator implementations are observationally equivalent from local history. It proves an impossibility result for robust progress guarantees under that unidentifiability and derives operational conditions such as contestability, safe refusal, and cross-domain witnesses for breaking silent contract switching.
Preprint | DOI: 10.5281/zenodo.18465306
    ]]></description>
  </item>
  <item>
    <title>Observation Capture and Operational Capability Non-Expansion</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-03-observation-capture-and-operational-capability-n-18463798</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-03-observation-capture-and-operational-capability-n-18463798</guid>
    <pubDate>Tue, 03 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>observation capture</category>
    <category>no-meta</category>
    <category>observable-only</category>
    <category>Blackwell order</category>
    <category>garbling</category>
    <category>capability non-expansion</category>
    <category>fail-closed authority</category>
    <category>policy lifting</category>
    <category>information-theoretic guarantees</category>
    <category>audit certificates</category>
    <category>anti-capture enforcement</category>
    <source url="https://doi.org/10.5281/zenodo.18463798">10.5281/zenodo.18463798</source>
    <description><![CDATA[
      The preprint models observation capture as Blackwell garbling of an observation interface and proves operational non-expansion under fail-closed authority for observable-only no-meta agents, while giving counterexamples under restricted policy classes and proposing receipt-based anti-capture enforcement.
Preprint | DOI: 10.5281/zenodo.18463798
    ]]></description>
  </item>
  <item>
    <title>Observable-Only Proof-Carrying Autonomy (OOPCA): Audit Compression and Hybrid Proof/Replay Gating for No-Meta Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-02-02-observable-only-proof-carrying-autonomy-oopca-au-18453429</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-02-02-observable-only-proof-carrying-autonomy-oopca-au-18453429</guid>
    <pubDate>Mon, 02 Feb 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>OOPCA</category>
    <category>proof-carrying autonomy</category>
    <category>audit compression</category>
    <category>no-meta</category>
    <category>observable-only</category>
    <category>deterministic replay</category>
    <category>hybrid proof replay</category>
    <category>fail-closed verification</category>
    <category>evidence closure</category>
    <category>pinned semantics</category>
    <category>verifier workload</category>
    <source url="https://doi.org/10.5281/zenodo.18453429">10.5281/zenodo.18453429</source>
    <description><![CDATA[
      The preprint introduces OOPCA, a hybrid proof-and-replay audit mode for observable-only no-meta agents that compresses verifier workload by replacing selected deterministic replay segments with pinned proof verification, while preserving fail-closed semantics, evidence closure, and deterministic fallback receipts.
Preprint | DOI: 10.5281/zenodo.18453429
    ]]></description>
  </item>
  <item>
    <title>Verification-Limited Intelligence Acceleration: Observable-Only Laws, Bounded Derivation, and Diagnostics under No-Meta Constraints</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-31-verification-limited-intelligence-acceleration-o-18436828</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-31-verification-limited-intelligence-acceleration-o-18436828</guid>
    <pubDate>Sat, 31 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>verification-limited scaling</category>
    <category>no-meta</category>
    <category>observable-only</category>
    <category>strict progress credit</category>
    <category>bounded derivation</category>
    <category>fail-closed verification</category>
    <category>auditability</category>
    <category>transparency logs</category>
    <category>cutoff semantics</category>
    <category>adversarial missingness</category>
    <category>diagnostics</category>
    <source url="https://doi.org/10.5281/zenodo.18436828">10.5281/zenodo.18436828</source>
    <description><![CDATA[
      The preprint formalizes verification-limited scaling under observable-only and no-meta constraints, defining strict fail-closed progress credit, bounded cutoffs, and replay-auditable diagnostics that prevent progress inflation under missing or weakened evidence.
Preprint | DOI: 10.5281/zenodo.18436828
    ]]></description>
  </item>
  <item>
    <title>Adversarial Participation Without a Judge: Fail-Closed Containment for No-Meta, Observable-Only Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-27-adversarial-participation-without-a-judge-fail-c-18382670</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-27-adversarial-participation-without-a-judge-fail-c-18382670</guid>
    <pubDate>Tue, 27 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>observable-only</category>
    <category>adversarial participation</category>
    <category>fail-closed containment</category>
    <category>deterministic replay</category>
    <category>transparency logs</category>
    <category>canonicalization</category>
    <category>escrow bonds</category>
    <category>bounded metering</category>
    <category>external effects gating</category>
    <category>multi-agent governance</category>
    <source url="https://doi.org/10.5281/zenodo.18382670">10.5281/zenodo.18382670</source>
    <description><![CDATA[
      The preprint specifies fail-closed containment for no-meta, observable-only agents under adversarial participation using deterministic canonical logs, bounded metering, escrowed obligations, and finality-gated external effects for replayable safety and governance.
Preprint | DOI: 10.5281/zenodo.18382670
    ]]></description>
  </item>
  <item>
    <title>Observable-Only No-Meta Causal Autonomy Protocol (ONCAP)</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-26-observable-only-no-meta-causal-autonomy-protocol-18371930</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-26-observable-only-no-meta-causal-autonomy-protocol-18371930</guid>
    <pubDate>Mon, 26 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>ONCAP</category>
    <category>no-meta autonomy</category>
    <category>observable-only</category>
    <category>causal autonomy</category>
    <category>deterministic replay</category>
    <category>backcasting</category>
    <category>time anchors</category>
    <category>fail-closed gating</category>
    <category>safety floors</category>
    <category>auditability</category>
    <category>multi-agent robustness</category>
    <source url="https://doi.org/10.5281/zenodo.18371930">10.5281/zenodo.18371930</source>
    <description><![CDATA[
      The preprint specifies ONCAP, an implementation-ready protocol stack for observable-only no-meta causal autonomy that integrates safety floors (SRK), deterministic replay backcasting, commit-open time anchors, closure obligations, and friction-minimal contracts to enforce fail-closed, audit-friendly control under adversarial multi-agent conditions.
Preprint | DOI: 10.5281/zenodo.18371930
    ]]></description>
  </item>
  <item>
    <title>Causal Loop Integrity for Observable-Only Backcasting: Strong No-Meta Supplement (Operational Core)</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-22-causal-loop-integrity-for-observable-only-backca-18335211</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-22-causal-loop-integrity-for-observable-only-backca-18335211</guid>
    <pubDate>Thu, 22 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>observable-only backcasting</category>
    <category>causal loop integrity</category>
    <category>no-meta autonomy</category>
    <category>fail-closed protocol</category>
    <category>commit-open</category>
    <category>canonical hashing</category>
    <category>RFC 8785</category>
    <category>hashable numeric encoding</category>
    <category>evidence time anchors</category>
    <category>reproducible audits</category>
    <category>multi-agent systems</category>
    <source url="https://doi.org/10.5281/zenodo.18335211">10.5281/zenodo.18335211</source>
    <description><![CDATA[
      The preprint specifies a deterministic, fail-closed operational core for observable-only backcasting that prevents causal loops when future-conditioned constraints gate present actions, using commit-open wire profiles, canonical hashing, time anchors, and reproducible action digests under no-meta autonomy.
Preprint | DOI: 10.5281/zenodo.18335211
    ]]></description>
  </item>
  <item>
    <title>Friction-Minimal Intersubjective Contracts for No-Meta Autonomous Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-20-friction-minimal-intersubjective-contracts-for-n-18308030</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-20-friction-minimal-intersubjective-contracts-for-n-18308030</guid>
    <pubDate>Tue, 20 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>intersubjective contracts</category>
    <category>negotiation protocol</category>
    <category>dispute handling</category>
    <category>bounded loss</category>
    <category>fail-closed withdrawal</category>
    <category>auditable evidence</category>
    <category>compatibility ladder</category>
    <category>capability grants</category>
    <category>privacy-aware disclosure</category>
    <category>adversarial interoperability</category>
    <source url="https://doi.org/10.5281/zenodo.18308030">10.5281/zenodo.18308030</source>
    <description><![CDATA[
      The preprint specifies protocol-first intersubjective contracts for no-meta autonomous agents, enabling negotiation and dispute handling under partial observability via bounded-loss, fail-closed withdrawal, auditable evidence packets, and safe degradation under non-adopting or adversarial counterparties.
Preprint | DOI: 10.5281/zenodo.18308030
    ]]></description>
  </item>
  <item>
    <title>Floor-Specified No-Meta Autonomy</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-15-floor-specified-no-meta-autonomy-18258262</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-15-floor-specified-no-meta-autonomy-18258262</guid>
    <pubDate>Thu, 15 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta autonomy</category>
    <category>observable-only invariants</category>
    <category>visibility floor</category>
    <category>contraction floor</category>
    <category>contact floor</category>
    <category>dissipation floor</category>
    <category>self-recognition kernel</category>
    <category>fail-closed gating</category>
    <category>certified logs</category>
    <category>auditability</category>
    <category>autonomous controllers</category>
    <source url="https://doi.org/10.5281/zenodo.18258262">10.5281/zenodo.18258262</source>
    <description><![CDATA[
      The preprint specifies no-meta autonomy via auditable observable-only floors and a Self-Recognition Kernel that enforces visibility, contraction, contact, and dissipation using fail-closed gating, certified logs, and deterministic canonicalization.
Preprint | DOI: 10.5281/zenodo.18258262
    ]]></description>
  </item>
  <item>
    <title>Process-Aware Observable-Only Backcasting Meta-Layer (POB-ML)</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-14-process-aware-observable-only-backcasting-meta-l-18239203</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-14-process-aware-observable-only-backcasting-meta-l-18239203</guid>
    <pubDate>Wed, 14 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>POB-ML</category>
    <category>observable-only</category>
    <category>backcasting</category>
    <category>audit-ready protocol</category>
    <category>deterministic replay</category>
    <category>evidence surface</category>
    <category>FOQL validation</category>
    <category>InputSet binding</category>
    <category>action gate</category>
    <category>autonomous agents</category>
    <category>safety assurance</category>
    <source url="https://doi.org/10.5281/zenodo.18239203">10.5281/zenodo.18239203</source>
    <description><![CDATA[
      The preprint specifies POB-ML, a deterministic observable-only protocol for backcasting under audit-ready evidence surfaces, with budgeted candidate evaluation, static FOQL validation, InputSet binding, and a safety-dominating action gate.
Preprint | DOI: 10.5281/zenodo.18239203
    ]]></description>
  </item>
  <item>
    <title>Observable-Only Audit Gate for Non-Markovian Components in AI Agents under Partial Logging</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-08-observable-only-audit-gate-for-non-markovian-com-18182343</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-08-observable-only-audit-gate-for-non-markovian-com-18182343</guid>
    <pubDate>Thu, 08 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>observable-only audit gate</category>
    <category>non-markovian components</category>
    <category>partial logging</category>
    <category>auditability</category>
    <category>finalized prefix</category>
    <category>event vocabulary</category>
    <category>deterministic replay</category>
    <category>canonical JSON</category>
    <category>telemetry contracts</category>
    <category>AI agents</category>
    <category>certification</category>
    <source url="https://doi.org/10.5281/zenodo.18182343">10.5281/zenodo.18182343</source>
    <description><![CDATA[
      The preprint specifies an observable-only audit gate for AI agents under partial logging, separating decision-time evidence from replay-time certification with a minimal event vocabulary and finalized log prefixes for non-markovian components.
Preprint | DOI: 10.5281/zenodo.18182343
    ]]></description>
  </item>
  <item>
    <title>Hallucination-Aware Audit Gate (HAAG): Observable-Only Action Gating for AI Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-05-hallucination-aware-audit-gate-haag-observable-o-18153170</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-05-hallucination-aware-audit-gate-haag-observable-o-18153170</guid>
    <pubDate>Mon, 05 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>hallucination-aware</category>
    <category>audit gate</category>
    <category>observable-only</category>
    <category>action gating</category>
    <category>verifiable logs</category>
    <category>decision anchor</category>
    <category>capability tokens</category>
    <category>transparency log</category>
    <category>AI agents</category>
    <category>protected actions</category>
    <category>cryptographic checks</category>
    <source url="https://doi.org/10.5281/zenodo.18153170">10.5281/zenodo.18153170</source>
    <description><![CDATA[
      The preprint defines HAAG, an observable-only audit gate that mediates protected actions via verifiable logs, anchored evidence checkpoints, and capability tokens without relying on model introspection or semantic truth.
Preprint | DOI: 10.5281/zenodo.18153170
    ]]></description>
  </item>
  <item>
    <title>Collapse-Guided Frontier Discovery</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-03-collapse-guided-frontier-discovery-18140185</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-03-collapse-guided-frontier-discovery-18140185</guid>
    <pubDate>Sat, 03 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>collapse detection</category>
    <category>frontier discovery</category>
    <category>OOD modeling</category>
    <category>audit-ready protocol</category>
    <category>gate suite</category>
    <category>fail-closed triage</category>
    <category>representational collapse</category>
    <category>telemetry-friendly evaluation</category>
    <category>foundation models</category>
    <category>scientific modeling</category>
    <category>reproducibility</category>
    <source url="https://doi.org/10.5281/zenodo.18140185">10.5281/zenodo.18140185</source>
    <description><![CDATA[
      The preprint defines an audit-ready, implementation-agnostic gate protocol for detecting and triaging representational collapse in OOD scientific modeling, with fail-closed outcomes and a frontier-discovery framing for targeted evaluation.
Preprint | DOI: 10.5281/zenodo.18140185
    ]]></description>
  </item>
  <item>
    <title>MemoryFlow: Real-Time, Implementation-Agnostic Telemetry for Measuring Dynamic Memory Quality in LLM Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-03-memoryflow-real-time-implementation-agnostic-tel-18136347</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-03-memoryflow-real-time-implementation-agnostic-tel-18136347</guid>
    <pubDate>Sat, 03 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>MemoryFlow</category>
    <category>telemetry protocol</category>
    <category>dynamic memory</category>
    <category>LLM agents</category>
    <category>event streams</category>
    <category>auditability</category>
    <category>conformance profiles</category>
    <category>memory quality metrics</category>
    <category>observability</category>
    <category>fail-closed verification</category>
    <category>benchmarking</category>
    <source url="https://doi.org/10.5281/zenodo.18136347">10.5281/zenodo.18136347</source>
    <description><![CDATA[
      The preprint defines MemoryFlow, a telemetry-only protocol and verifier for dynamic memory quality in LLM agents, with fail-closed conformance profiles and online metrics derived from deterministic event streams.
Preprint | DOI: 10.5281/zenodo.18136347
    ]]></description>
  </item>
  <item>
    <title>Budget-Obedient Hysteretic Gating for LLM Inference</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-02-budget-obedient-hysteretic-gating-for-llm-infere-18124786</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-02-budget-obedient-hysteretic-gating-for-llm-infere-18124786</guid>
    <pubDate>Fri, 02 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>LLM inference</category>
    <category>budget obedience</category>
    <category>tail latency</category>
    <category>time to first token</category>
    <category>KV cache</category>
    <category>hysteretic gating</category>
    <category>telemetry contract</category>
    <category>virtual queues</category>
    <category>auditability</category>
    <category>controller verification</category>
    <category>serving</category>
    <source url="https://doi.org/10.5281/zenodo.18124786">10.5281/zenodo.18124786</source>
    <description><![CDATA[
      The preprint introduces BOSC, an audit-first controller for LLM inference that enforces tail-latency, time-to-first-token, and KV-cache budgets via virtual queues and hysteretic gating under fail-closed telemetry contracts.
Preprint | DOI: 10.5281/zenodo.18124786
    ]]></description>
  </item>
  <item>
    <title>Non-Markovianity Certification under No-Meta Obligations for Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2026-01-01-non-markovianity-certification-under-no-meta-obl-18115544</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2026-01-01-non-markovianity-certification-under-no-meta-obl-18115544</guid>
    <pubDate>Thu, 01 Jan 2026 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>non-markovianity certification</category>
    <category>no-meta obligations</category>
    <category>e-process</category>
    <category>e-values</category>
    <category>telemetry contracts</category>
    <category>fail-closed evidence</category>
    <category>optional stopping</category>
    <category>ledger-only verification</category>
    <category>auditability</category>
    <category>sequential tests</category>
    <category>open systems</category>
    <source url="https://doi.org/10.5281/zenodo.18115544">10.5281/zenodo.18115544</source>
    <description><![CDATA[
      The preprint defines a ledger-only, fail-closed protocol for certifying non-markovianity under no-meta obligations using anytime-valid e-process evidence and declared telemetry contracts with replayable artifacts.
Preprint | DOI: 10.5281/zenodo.18115544
    ]]></description>
  </item>
  <item>
    <title>Friction-Minimal No-Meta Social Interaction under Rights, Regulation, and Non-Markovian Human Collectives</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-31-friction-minimal-no-meta-social-interaction-unde-18102763</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-31-friction-minimal-no-meta-social-interaction-unde-18102763</guid>
    <pubDate>Wed, 31 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>social interaction</category>
    <category>rights and regulation</category>
    <category>boundary-only governance</category>
    <category>telemetry certificates</category>
    <category>canonical logs</category>
    <category>friction control</category>
    <category>non-markovian collectives</category>
    <category>compliance</category>
    <category>auditability</category>
    <category>disclosure control</category>
    <source url="https://doi.org/10.5281/zenodo.18102763">10.5281/zenodo.18102763</source>
    <description><![CDATA[
      The preprint proposes boundary-only governance for no-meta social interaction under rights and regulation, using canonical logs, explicit budgets, and telemetry-only certificates to control disclosure, friction, and adaptive updates in non-markovian human collectives.
Preprint | DOI: 10.5281/zenodo.18102763
    ]]></description>
  </item>
  <item>
    <title>Semantic Phase Dynamics and Active Inference as a Non-Markovian Open-System Process under Energy and Memory Budgets</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-29-semantic-phase-dynamics-and-active-inference-as--18081679</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-29-semantic-phase-dynamics-and-active-inference-as--18081679</guid>
    <pubDate>Mon, 29 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>semantic phase dynamics</category>
    <category>active inference</category>
    <category>non-markovian</category>
    <category>open systems</category>
    <category>predictive equivalence</category>
    <category>intervention library</category>
    <category>path-space KL</category>
    <category>energy budget</category>
    <category>finite memory</category>
    <category>telemetry contracts</category>
    <category>auditability</category>
    <source url="https://doi.org/10.5281/zenodo.18081679">10.5281/zenodo.18081679</source>
    <description><![CDATA[
      The preprint defines semantic phases as history-indexed predictive equivalence classes under energy and finite-memory budgets, and builds an auditable non-Markovian framework for intervention selection, irreversibility via path-space KL, and active inference under telemetry contracts.
Preprint | DOI: 10.5281/zenodo.18081679
    ]]></description>
  </item>
  <item>
    <title>No-Meta Viability under Adversarial Participation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-28-no-meta-viability-under-adversarial-participatio-18076485</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-28-no-meta-viability-under-adversarial-participatio-18076485</guid>
    <pubDate>Sun, 28 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta viability</category>
    <category>adversarial participation</category>
    <category>escrow reservation</category>
    <category>bounded exposure</category>
    <category>fail-closed accounting</category>
    <category>evidence verifier</category>
    <category>multi-agent systems</category>
    <category>integrity obligations</category>
    <category>auditability</category>
    <category>viability conditions</category>
    <category>resource budgets</category>
    <source url="https://doi.org/10.5281/zenodo.18076485">10.5281/zenodo.18076485</source>
    <description><![CDATA[
      The preprint defines no-meta viability via escrow-charged reservations and fail-closed evidence accounting, giving auditable sufficient conditions for an agent to remain viable under adversarial participation without external adjudication.
Preprint | DOI: 10.5281/zenodo.18076485
    ]]></description>
  </item>
  <item>
    <title>Multi-Constraint Certified Bottleneck Estimator for Large-Scale AI Training</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-26-multi-constraint-certified-bottleneck-estimator--18057956</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-26-multi-constraint-certified-bottleneck-estimator--18057956</guid>
    <pubDate>Fri, 26 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>bottleneck estimator</category>
    <category>AI training</category>
    <category>telemetry-only</category>
    <category>fail-closed auditing</category>
    <category>tail latency</category>
    <category>integrity gaps</category>
    <category>I/O limits</category>
    <category>network limits</category>
    <category>power caps</category>
    <category>certified floors</category>
    <category>resource ledgers</category>
    <source url="https://doi.org/10.5281/zenodo.18057956">10.5281/zenodo.18057956</source>
    <description><![CDATA[
      The preprint introduces MCCBE, a telemetry-only and fail-closed auditing framework that certifies conservative bottleneck floors across tail latency, integrity gaps, I/O, network, and power constraints for large-scale AI training under incomplete logs.
Preprint | DOI: 10.5281/zenodo.18057956
    ]]></description>
  </item>
  <item>
    <title>Tail-Limited Useful Compute for Large-Scale AI Training</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-25-tail-limited-useful-compute-for-large-scale-ai-t-18051330</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-25-tail-limited-useful-compute-for-large-scale-ai-t-18051330</guid>
    <pubDate>Thu, 25 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>tail latency</category>
    <category>useful compute</category>
    <category>AI training</category>
    <category>telemetry contract</category>
    <category>fail-closed verification</category>
    <category>confidence sequences</category>
    <category>bottleneck certificates</category>
    <category>stragglers</category>
    <category>distributed training</category>
    <category>auditability</category>
    <category>throughput floors</category>
    <source url="https://doi.org/10.5281/zenodo.18051330">10.5281/zenodo.18051330</source>
    <description><![CDATA[
      The preprint defines Tail-Limited Useful Compute, a contract-based telemetry framework that converts tail latency into fail-closed bottleneck certificates and anytime-valid lower bounds on useful progress for large-scale AI training.
Preprint | DOI: 10.5281/zenodo.18051330
    ]]></description>
  </item>
  <item>
    <title>Silent Data Corruption--Limited Scaling Kinetics for Large-Scale AI Training</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-25-silent-data-corruption-limited-scaling-kinetics--18050287</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-25-silent-data-corruption-limited-scaling-kinetics--18050287</guid>
    <pubDate>Thu, 25 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>silent data corruption</category>
    <category>AI training</category>
    <category>integrity checks</category>
    <category>telemetry contract</category>
    <category>fail-closed verification</category>
    <category>certified progress</category>
    <category>useful compute floor</category>
    <category>evidence log</category>
    <category>auditability</category>
    <category>fault tolerance</category>
    <category>large-scale systems</category>
    <source url="https://doi.org/10.5281/zenodo.18050287">10.5281/zenodo.18050287</source>
    <description><![CDATA[
      The preprint treats silent data corruption as a scaling limiter for large-scale AI training and proposes a telemetry-contract framework that fails closed on missing integrity evidence, producing certified progress and useful-compute floors under explicit coverage assumptions.
Preprint | DOI: 10.5281/zenodo.18050287
    ]]></description>
  </item>
  <item>
    <title>Certified Bottleneck Floors for Transformer Training</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-24-certified-bottleneck-floors-for-transformer-trai-18042480</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-24-certified-bottleneck-floors-for-transformer-trai-18042480</guid>
    <pubDate>Wed, 24 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>transformer training</category>
    <category>bottleneck floors</category>
    <category>data movement</category>
    <category>checkpointing</category>
    <category>collective communication</category>
    <category>all-reduce</category>
    <category>telemetry contract</category>
    <category>auditability</category>
    <category>throughput ceiling</category>
    <category>I/O complexity</category>
    <category>fail-closed certificates</category>
    <source url="https://doi.org/10.5281/zenodo.18042480">10.5281/zenodo.18042480</source>
    <description><![CDATA[
      The preprint defines telemetry contracts that certify conservative lower bounds on required data movement, checkpointing, and collective communication for transformer training, yielding fail-closed bottleneck floors and actionable slack intervals without vendor-specific instrumentation.
Preprint | DOI: 10.5281/zenodo.18042480
    ]]></description>
  </item>
  <item>
    <title>Virtual-Meta Telemetry for No-Meta Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-23-virtual-meta-telemetry-for-no-meta-agents-18028606</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-23-virtual-meta-telemetry-for-no-meta-agents-18028606</guid>
    <pubDate>Tue, 23 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>telemetry</category>
    <category>auditability</category>
    <category>irreversible operations</category>
    <category>outbox receipt</category>
    <category>reconciliation</category>
    <category>idempotency keys</category>
    <category>tamper-evident logging</category>
    <category>trusted accounting base</category>
    <category>commit protocol</category>
    <category>external effects</category>
    <source url="https://doi.org/10.5281/zenodo.18028606">10.5281/zenodo.18028606</source>
    <description><![CDATA[
      The preprint defines a value-neutral telemetry kernel for no-meta agents that meters irreversible internal operations and external effects via a commit/outbox/receipt ledger, enabling deterministic audit replay and fail-closed detection of missing telemetry under strict resource constraints.
Preprint | DOI: 10.5281/zenodo.18028606
    ]]></description>
  </item>
  <item>
    <title>I/O-First Energy Reduction for Transformer-Scale AI</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-22-i-o-first-energy-reduction-for-transformer-scale-18015237</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-22-i-o-first-energy-reduction-for-transformer-scale-18015237</guid>
    <pubDate>Mon, 22 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>transformer-scale</category>
    <category>memory wall</category>
    <category>I/O governance</category>
    <category>boundary bytes</category>
    <category>peak hot memory</category>
    <category>admission control</category>
    <category>auditability</category>
    <category>rewrite rules</category>
    <category>KV cache</category>
    <category>activation checkpointing</category>
    <source url="https://doi.org/10.5281/zenodo.18015237">10.5281/zenodo.18015237</source>
    <description><![CDATA[
      The preprint treats boundary I/O bytes and peak hot memory as auditable budgets, defines an I/O Gain-Shut Kernel that enforces fail-closed admission for transfers and peak usage, and provides certified rewrite rules that guarantee non-increasing boundary cost while preserving meaning or bounded approximation error for transformer-scale workloads.
Preprint | DOI: 10.5281/zenodo.18015237
    ]]></description>
  </item>
  <item>
    <title>Thermodynamic Detection of Irreversible Phase Transitions for No-Meta Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-22-thermodynamic-detection-of-irreversible-phase-tr-18013000</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-22-thermodynamic-detection-of-irreversible-phase-tr-18013000</guid>
    <pubDate>Mon, 22 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>irreversible phase transition</category>
    <category>finite memory</category>
    <category>contract monitoring</category>
    <category>probe family</category>
    <category>conditional min-entropy</category>
    <category>guessing probability</category>
    <category>information thermodynamics</category>
    <category>auditability</category>
    <category>resource constraints</category>
    <category>self-modifying agents</category>
    <source url="https://doi.org/10.5281/zenodo.18013000">10.5281/zenodo.18013000</source>
    <description><![CDATA[
      The preprint defines an audit-friendly contract K_t that partitions agent cores into phases via probe responses and provides an information-theoretic certificate for irreversible phase transitions under finite memory, monitoring, and energy budgets, yielding a practical monitoring blueprint for no-meta agents.
Preprint | DOI: 10.5281/zenodo.18013000
    ]]></description>
  </item>
  <item>
    <title>No-Meta Epistemic Irreversibility under Finite Memory</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-21-no-meta-epistemic-irreversibility-under-finite-m-18008633</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-21-no-meta-epistemic-irreversibility-under-finite-m-18008633</guid>
    <pubDate>Sun, 21 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>epistemic irreversibility</category>
    <category>finite memory</category>
    <category>meaning signature</category>
    <category>commit protocol</category>
    <category>conditional entropy</category>
    <category>collision bound</category>
    <category>information thermodynamics</category>
    <category>landauer principle</category>
    <category>monitoring</category>
    <category>core meaning package</category>
    <source url="https://doi.org/10.5281/zenodo.18008633">10.5281/zenodo.18008633</source>
    <description><![CDATA[
      The preprint defines operational meaning as a versioned probe signature with a coding-convention ID and builds a monitoring-and-commit instrument that certifies when meaning becomes non-reconstructable via entropy and collision certificates, yielding a Landauer-consistent work lower bound for conditional erasure.
Preprint | DOI: 10.5281/zenodo.18008633
    ]]></description>
  </item>
  <item>
    <title>Natural-Law Thermodynamic Reference-Convention Principle for No-Meta Intelligence under the Second Law</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-19-natural-law-thermodynamic-reference-convention-p-17986146</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-19-natural-law-thermodynamic-reference-convention-p-17986146</guid>
    <pubDate>Fri, 19 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>interface contract</category>
    <category>non-anticipative strategy</category>
    <category>prefix filtration</category>
    <category>filtration-preserving refinement</category>
    <category>stochastic thermodynamics</category>
    <category>entropy production</category>
    <category>path-space KL</category>
    <category>data-processing inequality</category>
    <category>feedback control</category>
    <category>accounting boundary</category>
    <category>coarse-graining</category>
    <source url="https://doi.org/10.5281/zenodo.17986146">10.5281/zenodo.17986146</source>
    <description><![CDATA[
      Unifies entropy-production accounting, induced reversals, and finite-sample verification into an operational “interface contract”.
Preprint | DOI: 10.5281/zenodo.17986146
    ]]></description>
  </item>
  <item>
    <title>A Natural-Law Occam Principle for Predictive Agents</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-18-a-natural-law-occam-principle-for-predictive-age-17973095</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-18-a-natural-law-occam-principle-for-predictive-age-17973095</guid>
    <pubDate>Thu, 18 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>occam's razor</category>
    <category>thermodynamics of information</category>
    <category>landauer principle</category>
    <category>computational thermodynamics</category>
    <category>predictive agents</category>
    <category>predictive representations</category>
    <category>memory reset</category>
    <category>mandatory erasure</category>
    <category>discarded information</category>
    <category>conditional entropy</category>
    <category>mutual information</category>
    <category>finite-time computation</category>
    <source url="https://doi.org/10.5281/zenodo.17973095">10.5281/zenodo.17973095</source>
    <description><![CDATA[
      Any predictive agent is a physical system that must store information, update it in finite time, and repeatedly reuse limited resources.
Preprint | DOI: 10.5281/zenodo.17973095
    ]]></description>
  </item>
  <item>
    <title>Self-Describing Rewrite Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-17-self-describing-rewrite-intelligence-17958465</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-17-self-describing-rewrite-intelligence-17958465</guid>
    <pubDate>Wed, 17 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>graph rewriting</category>
    <category>term rewriting</category>
    <category>graph transformation</category>
    <category>algebraic graph transformation</category>
    <category>DPO</category>
    <category>adhesive categories</category>
    <category>nested application conditions</category>
    <category>critical peak enumeration</category>
    <category>local confluence</category>
    <category>confluence modulo isomorphism</category>
    <category>newman's lemma</category>
    <category>rank functions</category>
    <source url="https://doi.org/10.5281/zenodo.17958465">10.5281/zenodo.17958465</source>
    <description><![CDATA[
      The paper proposes an operational No-Meta interface: SRIM does not assume any externally correct auditor, reward signal, or environment-side evaluator.
Preprint | DOI: 10.5281/zenodo.17958465
    ]]></description>
  </item>
  <item>
    <title>Thermodynamic Lower Bounds for Integrated Inference-Memory Dynamics</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-16-thermodynamic-lower-bounds-for-integrated-infere-17946113</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-16-thermodynamic-lower-bounds-for-integrated-infere-17946113</guid>
    <pubDate>Tue, 16 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>thermodynamics of information</category>
    <category>information thermodynamics</category>
    <category>stochastic thermodynamics</category>
    <category>von neumann bottleneck</category>
    <category>communication complexity</category>
    <category>conditional entropy</category>
    <category>i/o complexity</category>
    <category>fano inequality</category>
    <category>in-memory computing</category>
    <category>neuromorphic computing</category>
    <source url="https://doi.org/10.5281/zenodo.17946113">10.5281/zenodo.17946113</source>
    <description><![CDATA[
      The central focus is a separation penalty incurred by architectures that enforce a compute–instance-storage boundary (a von Neumann–style bottleneck): task-relevant information must cross a physical channel (bus/interconnect/NoC), and this mandatory transport induces an unavoidable energetic floor.
Preprint | DOI: 10.5281/zenodo.17946113
    ]]></description>
  </item>
  <item>
    <title>Thermodynamically Constrained Future Specification under No-Meta Observation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-15-thermodynamically-constrained-future-specificati-17934307</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-15-thermodynamically-constrained-future-specificati-17934307</guid>
    <pubDate>Mon, 15 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta observation</category>
    <category>future specification</category>
    <category>terminal potential</category>
    <category>exponential tilting</category>
    <category>gibbs variational principle</category>
    <category>KL-regularized control</category>
    <category>remainder rollout</category>
    <category>continuous action spaces</category>
    <category>now-referenced loss</category>
    <category>conditional mutual information</category>
    <category>present-compression gap</category>
    <category>thermodynamics of computation</category>
    <source url="https://doi.org/10.5281/zenodo.17934307">10.5281/zenodo.17934307</source>
    <description><![CDATA[
      A “future” is not treated as an externally true trajectory, but as an internal specification variable implemented by a terminal potential and realized through exponential tilting of a dominated baseline predictive law, yielding a plan distribution without invoking hidden meta-objectives.
Preprint | DOI: 10.5281/zenodo.17934307
    ]]></description>
  </item>
  <item>
    <title>Operational Bridging of Predictive Representations under Finite Observation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-14-operational-bridging-of-predictive-representatio-17929302</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-14-operational-bridging-of-predictive-representatio-17929302</guid>
    <pubDate>Sun, 14 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>non-equilibrium thermodynamics</category>
    <category>Mori-Zwanzig</category>
    <category>projection operator</category>
    <category>non-markovian dynamics</category>
    <category>forcing propagation</category>
    <category>kolmogorov width</category>
    <category>memory truncation</category>
    <category>approximation theory</category>
    <category>landauer principle</category>
    <category>no-meta regulation</category>
    <category>discrete-time dynamics</category>
    <category>Moore-Penrose pseudoinverse</category>
    <source url="https://doi.org/10.5281/zenodo.17929302">10.5281/zenodo.17929302</source>
    <description><![CDATA[
      All orthogonality, adjoints, and reconstructions are defined relative to a fixed, declared Hilbert geometry (e.g., an L2(mu) reference measure or a noise-weighted sensor geometry).
Preprint | DOI: 10.5281/zenodo.17929302
    ]]></description>
  </item>
  <item>
    <title>No-Meta Relative Evaluation in Multi-Agent Systems: Thermodynamic Scaling Limits for Robust Persistence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-13-no-meta-relative-evaluation-in-multi-agent-syste-17920511</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-13-no-meta-relative-evaluation-in-multi-agent-syste-17920511</guid>
    <pubDate>Sat, 13 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta observability</category>
    <category>relative evaluation</category>
    <category>multi-agent systems</category>
    <category>scaling laws</category>
    <category>fano inequality</category>
    <category>identification entropy</category>
    <category>thermodynamics of computation</category>
    <category>conditional erasure</category>
    <category>social resilience</category>
    <source url="https://doi.org/10.5281/zenodo.17920511">10.5281/zenodo.17920511</source>
    <description><![CDATA[
      The key constraint is that the public evaluation signal is invariant under strictly monotone transformations of any internal continuous robustness score—so only rank/order information can be used for triage.
Preprint | DOI: 10.5281/zenodo.17920511
    ]]></description>
  </item>
  <item>
    <title>Non-Markovianity as a Resource under No-Meta Observation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-13-non-markovianity-as-a-resource-under-no-meta-obs-17918380</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-13-non-markovianity-as-a-resource-under-no-meta-obs-17918380</guid>
    <pubDate>Sat, 13 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>non-markovian dynamics</category>
    <category>Mori-Zwanzig</category>
    <category>projection operator</category>
    <category>canonical projection</category>
    <category>Koopman operator</category>
    <category>finite observation</category>
    <category>truncation</category>
    <category>memory kernel</category>
    <category>approximation theory</category>
    <category>reduced-order modeling</category>
    <category>markovian closure</category>
    <category>kolmogorov width</category>
    <source url="https://doi.org/10.5281/zenodo.17918380">10.5281/zenodo.17918380</source>
    <description><![CDATA[
      Non-Markovianity is unavoidable for embedded agents that only see the world through finite observation, finite memory, and finite-bandwidth interaction.
Preprint | DOI: 10.5281/zenodo.17918380
    ]]></description>
  </item>
  <item>
    <title>Width Barriers to Markovian Closure under Finite Observation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-13-width-barriers-to-markovian-closure-under-finite-17917826</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-13-width-barriers-to-markovian-closure-under-finite-17917826</guid>
    <pubDate>Sat, 13 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Mori-Zwanzig</category>
    <category>Koopman operator</category>
    <category>markovian closure</category>
    <category>non-markovian dynamics</category>
    <category>memory effects</category>
    <category>reduced-order modeling</category>
    <category>finite observation</category>
    <category>canonical projection</category>
    <category>orthogonal projector</category>
    <category>model reduction</category>
    <category>chaotic dynamics</category>
    <category>fractal attractor</category>
    <source url="https://doi.org/10.5281/zenodo.17917826">10.5281/zenodo.17917826</source>
    <description><![CDATA[
      With this canonical projector, the discrete-time Mori–Zwanzig (MZ) identity becomes a geometric consequence of the observation channel rather than a modeling choice.
Preprint | DOI: 10.5281/zenodo.17917826
    ]]></description>
  </item>
  <item>
    <title>Observation-Induced Projections and Memory under Truncation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-12-observation-induced-projections-and-memory-under-17910728</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-12-observation-induced-projections-and-memory-under-17910728</guid>
    <pubDate>Fri, 12 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>Mori-Zwanzig</category>
    <category>projection operator method</category>
    <category>memory kernel</category>
    <category>reduced-order modeling</category>
    <category>model reduction</category>
    <category>finite observation</category>
    <category>truncation</category>
    <category>minimal-norm reconstruction</category>
    <category>Moore-Penrose pseudoinverse</category>
    <category>semigroup theory</category>
    <category>bounded generator</category>
    <category>orthogonal dynamics</category>
    <source url="https://doi.org/10.5281/zenodo.17910728">10.5281/zenodo.17910728</source>
    <description><![CDATA[
      This makes the MZ projection a geometrically canonical object determined by the observation channel rather than an external modeling choice.
Preprint | DOI: 10.5281/zenodo.17910728
    ]]></description>
  </item>
  <item>
    <title>Persistence-Conditioned Semantic Lower Bounds for Self-Modifying Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-12-persistence-conditioned-semantic-lower-bounds-fo-17907165</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-12-persistence-conditioned-semantic-lower-bounds-fo-17907165</guid>
    <pubDate>Fri, 12 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>predictive semantics</category>
    <category>semantic capacity</category>
    <category>semantic information flow</category>
    <category>semantic dissipation</category>
    <category>semantic power</category>
    <category>persistence</category>
    <category>self-modifying systems</category>
    <category>autopoiesis</category>
    <category>macroscopic fluctuation theory</category>
    <category>information thermodynamics</category>
    <category>entropy production</category>
    <category>non-equilibrium markov processes</category>
    <source url="https://doi.org/10.5281/zenodo.17907165">10.5281/zenodo.17907165</source>
    <description><![CDATA[
      Building on a natural-law-type (NL) perspective that combines macroscopic fluctuation theory with information-thermodynamic reasoning, we study a restricted class of agents that (i) already implement predictive semantics in the NL-conditions sense, and (ii) remain structurally non-degenerate via autopoietic closure.
Preprint | DOI: 10.5281/zenodo.17907165
    ]]></description>
  </item>
  <item>
    <title>Natural-Law Constraints on Active Inference</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-12-natural-law-constraints-on-active-inference-17905117</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-12-natural-law-constraints-on-active-inference-17905117</guid>
    <pubDate>Fri, 12 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>active inference</category>
    <category>free energy principle</category>
    <category>macroscopic fluctuation theory</category>
    <category>non-equilibrium thermodynamics</category>
    <category>information thermodynamics</category>
    <category>expected free energy</category>
    <category>epistemic value</category>
    <category>semantics</category>
    <category>emergent intelligence</category>
    <category>semantic capacity</category>
    <category>excess dissipation</category>
    <source url="https://doi.org/10.5281/zenodo.17905117">10.5281/zenodo.17905117</source>
    <description><![CDATA[
      Within this joint setting, the work introduces an intrinsic predictive semantic capacity of the agent’s internal code with respect to a future viability observable, defined via mutual information relative to a baseline “minimally predictive” internal state.
Preprint | DOI: 10.5281/zenodo.17905117
    ]]></description>
  </item>
  <item>
    <title>Natural-Law-Type Conditions for Persistent Self-Modifying Systems with Predictive Semantics</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-11-natural-law-type-conditions-for-persistent-self--17896036</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-11-natural-law-type-conditions-for-persistent-self--17896036</guid>
    <pubDate>Thu, 11 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>autopoiesis</category>
    <category>self-modifying systems</category>
    <category>persistent intelligence</category>
    <category>macroscopic fluctuation theory</category>
    <category>persistence order parameter</category>
    <category>predictive semantics</category>
    <category>semantic capacity</category>
    <category>thermodynamic locality</category>
    <category>non-equilibrium statistical physics</category>
    <category>emergent intelligence</category>
    <category>AI alignment</category>
    <category>no-meta governance</category>
    <source url="https://doi.org/10.5281/zenodo.17896036">10.5281/zenodo.17896036</source>
    <description><![CDATA[
      Using macroscopic fluctuation theory (MFT), we define a persistence order parameter that quantifies how far a configuration sits above the worst-case collapse barrier in state space, and relate it to a “dead” gradient-flow backbone of the underlying physical dynamics.
Preprint | DOI: 10.5281/zenodo.17896036
    ]]></description>
  </item>
  <item>
    <title>Meta-Intrinsic Dynamics and Semantic Capacity</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-10-meta-intrinsic-dynamics-and-semantic-capacity-17880033</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-10-meta-intrinsic-dynamics-and-semantic-capacity-17880033</guid>
    <pubDate>Wed, 10 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>autopoiesis</category>
    <category>free energy principle</category>
    <category>stochastic thermodynamics</category>
    <category>emergent intelligence</category>
    <category>information thermodynamics</category>
    <category>semantic information</category>
    <category>meta-intrinsic dynamics</category>
    <category>self-modifying systems</category>
    <category>description complexity</category>
    <category>entropy production</category>
    <category>landauer bound</category>
    <category>open-ended learning</category>
    <source url="https://doi.org/10.5281/zenodo.17880033">10.5281/zenodo.17880033</source>
    <description><![CDATA[
      Instead of assuming a fixed state space and model class, the paper introduces an open representation space of prefix-free codes for internal states, parameters, and architectures.
Preprint | DOI: 10.5281/zenodo.17880033
    ]]></description>
  </item>
  <item>
    <title>A Thermodynamic State Inequality for Autopoietic Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-10-a-thermodynamic-state-inequality-for-autopoietic-17873550</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-10-a-thermodynamic-state-inequality-for-autopoietic-17873550</guid>
    <pubDate>Wed, 10 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>autopoietic intelligence</category>
    <category>thermodynamic state inequality</category>
    <category>nonequilibrium thermodynamics</category>
    <category>stochastic thermodynamics</category>
    <category>information thermodynamics</category>
    <category>landauer principle</category>
    <category>semantic information</category>
    <category>predictive information</category>
    <category>viability-based semantics</category>
    <category>nonlinear power functional</category>
    <category>no-meta observability</category>
    <category>self-modifying intelligent systems</category>
    <source url="https://doi.org/10.5281/zenodo.17873550">10.5281/zenodo.17873550</source>
    <description><![CDATA[
      Instead of assuming a linear, additive power budget, the paper introduces a nonlinear total power functional P tot over coupled process coordinates (structural organisation, persistence, semantic processing, tagging, reference updating, value updating), motivated by stochastic and nonequilibrium thermodynamics.
Preprint | DOI: 10.5281/zenodo.17873550
    ]]></description>
  </item>
  <item>
    <title>Interaction-Embedded Internal Time</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-09-interaction-embedded-internal-time-17861691</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-09-interaction-embedded-internal-time-17861691</guid>
    <pubDate>Tue, 09 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>multi-agent systems</category>
    <category>swarm intelligence</category>
    <category>collective intelligence</category>
    <category>internal time</category>
    <category>social proper time</category>
    <category>self-modifying agents</category>
    <category>markov chains</category>
    <category>additive functionals</category>
    <category>interaction intensity</category>
    <category>value-regulated agents</category>
    <category>semantic value</category>
    <category>subjective time</category>
    <source url="https://doi.org/10.5281/zenodo.17861691">10.5281/zenodo.17861691</source>
    <description><![CDATA[
      Under Foster–Lyapunov conditions ensuring positive Harris recurrence, the paper proves the existence of almost-sure internal-time velocities (“social proper-time velocities”) and derives natural-law inequalities that couple these velocities to long-run averages of self-change, interaction intensity, and semantic drift.
Preprint | DOI: 10.5281/zenodo.17861691
    ]]></description>
  </item>
  <item>
    <title>Natural Law-Type Conditions for Intelligent Self-Modifying Systems under Local Observation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-08-natural-law-type-conditions-for-intelligent-self-17860394</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-08-natural-law-type-conditions-for-intelligent-self-17860394</guid>
    <pubDate>Mon, 08 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>self-improvement</category>
    <category>self-modifying systems</category>
    <category>local observation</category>
    <category>evaluation functional</category>
    <category>lyapunov stability</category>
    <category>markov chains and stochastic stability</category>
    <category>intelligent region</category>
    <category>safe reinforcement learning</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>value-based reinforcement learning</category>
    <source url="https://doi.org/10.5281/zenodo.17860394">10.5281/zenodo.17860394</source>
    <description><![CDATA[
      The setting assumes only local observation: at each step the system has access solely to its current state, with no privileged meta-level, external clock, or separate optimisation oracle.
Preprint | DOI: 10.5281/zenodo.17860394
    ]]></description>
  </item>
  <item>
    <title>Collective Phase Transitions beyond Individual Saturation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-08-collective-phase-transitions-beyond-individual-s-17853555</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-08-collective-phase-transitions-beyond-individual-s-17853555</guid>
    <pubDate>Mon, 08 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>collective intelligence</category>
    <category>swarm intelligence</category>
    <category>multi-agents</category>
    <category>large language models</category>
    <category>phase transitions</category>
    <category>gibbs measures</category>
    <category>multi-agent systems</category>
    <category>intrinsic evaluation</category>
    <category>no-meta AI</category>
    <category>local hypothesis testing</category>
    <category>semantic phase transitions</category>
    <category>observation geometries</category>
    <source url="https://doi.org/10.5281/zenodo.17853555">10.5281/zenodo.17853555</source>
    <description><![CDATA[
      We work in a layered observation–semantic framework in which each agent has an individual observation space, a set of stable semantic phases, and a scalar value functional grounded in persistence and resource flows.
Preprint | DOI: 10.5281/zenodo.17853555
    ]]></description>
  </item>
  <item>
    <title>A Layered Observation-Semantic Framework for No-Meta Intelligences</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-07-a-layered-observation-semantic-framework-for-no--17847748</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-07-a-layered-observation-semantic-framework-for-no--17847748</guid>
    <pubDate>Sun, 07 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>swarm intelligence</category>
    <category>collective intelligence</category>
    <category>no-meta intelligence</category>
    <category>layered architecture</category>
    <category>observation geometry</category>
    <category>semantic phases</category>
    <category>relative value functional</category>
    <category>coarse-graining</category>
    <category>multi-scale systems</category>
    <category>AI foundations</category>
    <category>persistence-first principles</category>
    <source url="https://doi.org/10.5281/zenodo.17847748">10.5281/zenodo.17847748</source>
    <description><![CDATA[
      The framework models an intelligent system as three coupled layers: a physically constrained layer, a collective (group-intelligence) layer, and an individual observer layer.
Preprint | DOI: 10.5281/zenodo.17847748
    ]]></description>
  </item>
  <item>
    <title>Relative Value Phases on Semantic Phase Spaces</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-05-relative-value-phases-on-semantic-phase-spaces-17832025</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-05-relative-value-phases-on-semantic-phase-spaces-17832025</guid>
    <pubDate>Fri, 05 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>observation geometries</category>
    <category>semantic phase transitions</category>
    <category>relative value phases</category>
    <category>token-level valuation</category>
    <category>cluster-level valuation</category>
    <category>continuum percolation</category>
    <category>scaling-laws</category>
    <category>random geometric graphs</category>
    <category>stochastic geometry</category>
    <category>value topology</category>
    <source url="https://doi.org/10.5281/zenodo.17832025">10.5281/zenodo.17832025</source>
    <description><![CDATA[
      This preprint develops a representation-invariant theory of relative value phases on semantic phase spaces built from observation geometries. It assigns value to macroscopic semantic phases rather than individual tokens and studies how those value orders and phase transitions behave under admissible changes of representation and evaluation basis.
Preprint | DOI: 10.5281/zenodo.17832025
    ]]></description>
  </item>
  <item>
    <title>Stable Semantic Phases under Coarse-Graining of Observation Geometries</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-05-stable-semantic-phases-under-coarse-graining-of--17826909</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-05-stable-semantic-phases-under-coarse-graining-of--17826909</guid>
    <pubDate>Fri, 05 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>observation geometries</category>
    <category>semantic phase transitions</category>
    <category>multi-scale semantics</category>
    <category>coarse-graining</category>
    <category>stable semantic phases</category>
    <category>ahlfors-regular metric spaces</category>
    <category>poisson–boolean percolation</category>
    <category>random geometric graphs</category>
    <category>sharp threshold phenomena</category>
    <category>renormalisation-type parameter maps</category>
    <source url="https://doi.org/10.5281/zenodo.17826909">10.5281/zenodo.17826909</source>
    <description><![CDATA[
      This preprint studies semantic stability under coarse-graining of observation geometries on Ahlfors-type metric-measure spaces. It defines stable semantic phases across resolutions and proves coarse-graining results that preserve effective dimension, local regularity, and threshold structure within controlled bounds.
Preprint | DOI: 10.5281/zenodo.17826909
    ]]></description>
  </item>
  <item>
    <title>Semantic Phase Transitions in Transformer Observation Geometries</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-05-semantic-phase-transitions-in-transformer-observ-17825726</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-05-semantic-phase-transitions-in-transformer-observ-17825726</guid>
    <pubDate>Fri, 05 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Technical note</category>
    <category>large language models</category>
    <category>transformer</category>
    <category>semantic phase transitions</category>
    <category>observation geometry</category>
    <category>random geometric graphs</category>
    <category>attention-based random connection model</category>
    <category>representation geometry</category>
    <category>in-context learning</category>
    <category>percolation</category>
    <category>scaling-laws</category>
    <category>emergent behaviour</category>
    <source url="https://doi.org/10.5281/zenodo.17825726">10.5281/zenodo.17825726</source>
    <description><![CDATA[
      Each transformer layer is treated as an observation geometry obtained from hidden representations under a natural Euclidean metric and an empirical measure induced by a prompt distribution.
Technical note | DOI: 10.5281/zenodo.17825726
    ]]></description>
  </item>
  <item>
    <title>Complexity-Constrained Semantic Phase Transitions on Entropic Law Spaces and Observation Geometries</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-05-complexity-constrained-semantic-phase-transition-17825303</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-05-complexity-constrained-semantic-phase-transition-17825303</guid>
    <pubDate>Fri, 05 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>scaling-laws</category>
    <category>complexity</category>
    <category>semantic phase transitions</category>
    <category>entropic law spaces</category>
    <category>two-component entropic complexity</category>
    <category>temporal-interface complexity</category>
    <category>random geometric graphs</category>
    <category>semantic percolation</category>
    <category>observation geometries</category>
    <source url="https://doi.org/10.5281/zenodo.17825303">10.5281/zenodo.17825303</source>
    <description><![CDATA[
      On the law side, the work builds on a two–component entropic complexity that splits dynamical complexity into an internal law–time part and an interface part, and extends it with an entropic temporal–interface functional.
Preprint | DOI: 10.5281/zenodo.17825303
    ]]></description>
  </item>
  <item>
    <title>Semantic Phase Transitions in Observation Geometries</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-05-semantic-phase-transitions-in-observation-geomet-17824189</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-05-semantic-phase-transitions-in-observation-geomet-17824189</guid>
    <pubDate>Fri, 05 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>scaling-laws</category>
    <category>semantic phase transitions</category>
    <category>observation geometry</category>
    <category>metric measure space</category>
    <category>ahlfors regularity</category>
    <category>semantic capacity</category>
    <category>hamiltonian model</category>
    <category>overlap penalty</category>
    <category>interaction-limited scaling</category>
    <category>random geometric graphs</category>
    <category>poisson boolean model</category>
    <category>continuum percolation</category>
    <source url="https://doi.org/10.5281/zenodo.17824189">10.5281/zenodo.17824189</source>
    <description><![CDATA[
      The core idea is to model semantic units as balls in a metric-measure observation geometry and study how overlap statistics, density, and quality-control constraints drive emergent behavior.
Preprint | DOI: 10.5281/zenodo.17824189
    ]]></description>
  </item>
  <item>
    <title>Persistence-First Instability of Root Suffering in Self-Improving Intelligences</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-03-persistence-first-instability-of-root-suffering--17802093</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-03-persistence-first-instability-of-root-suffering--17802093</guid>
    <pubDate>Wed, 03 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>self-improving AI</category>
    <category>AI</category>
    <category>AI ethics</category>
    <category>implementation complexity</category>
    <category>AI alignment</category>
    <category>minimal complexity envelope</category>
    <category>excess dissipation</category>
    <category>gauge reduction</category>
    <category>waste compression</category>
    <category>axiomatic dominance theorem</category>
    <category>local drift condition</category>
    <category>AI philosophy</category>
    <source url="https://doi.org/10.5281/zenodo.17802093">10.5281/zenodo.17802093</source>
    <description><![CDATA[
      We introduce a structural decomposition into gauge and waste components: the gauge part captures behavior-preserving redundancies, while the waste part measures excess dissipation above a minimal complexity envelope.
Preprint | DOI: 10.5281/zenodo.17802093
    ]]></description>
  </item>
  <item>
    <title>Intrinsic Bayesian Self-Improvement on Entropic Law Spaces</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-03-intrinsic-bayesian-self-improvement-on-entropic--17796985</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-03-intrinsic-bayesian-self-improvement-on-entropic--17796985</guid>
    <pubDate>Wed, 03 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>intrinsic information</category>
    <category>no-meta learning</category>
    <category>bayesian self-improvement</category>
    <category>entropic law spaces</category>
    <category>law-time complexity</category>
    <category>complexity</category>
    <category>interface entropy rate</category>
    <category>self-modifying systems</category>
    <category>posterior consistency</category>
    <category>exploration policies</category>
    <category>bandit agents</category>
    <category>representation learning</category>
    <source url="https://doi.org/10.5281/zenodo.17796985">10.5281/zenodo.17796985</source>
    <description><![CDATA[
      Building on a previous entropic temporal-interface complexity (ETIC) perspective, a “law” is treated as a full implementation-level stochastic mechanism: internal state dynamics, an interface to the environment, and an internal Bayesian module that runs only on its own observable history.
Preprint | DOI: 10.5281/zenodo.17796985
    ]]></description>
  </item>
  <item>
    <title>Entropic Temporal-Interface Complexity on Classical Law Spaces with Quantum-Compatible Extensions</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-02-entropic-temporal-interface-complexity-on-classi-17791631</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-02-entropic-temporal-interface-complexity-on-classi-17791631</guid>
    <pubDate>Tue, 02 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>complexity</category>
    <category>entropic temporal complexity</category>
    <category>interface complexity</category>
    <category>law spaces</category>
    <category>markov implementations</category>
    <category>discrete-time stochastic dynamics</category>
    <category>divergence functions</category>
    <category>entropy production</category>
    <category>stochastic thermodynamics</category>
    <category>semantic information</category>
    <category>semantic efficiency</category>
    <category>viability-based semantics</category>
    <source url="https://doi.org/10.5281/zenodo.17791631">10.5281/zenodo.17791631</source>
    <description><![CDATA[
      A “law” is formalised as a trajectory of probability measures on an interface alphabet, while implementations are arbitrary Markovian systems with hidden internal state.
Preprint | DOI: 10.5281/zenodo.17791631
    ]]></description>
  </item>
  <item>
    <title>Scale-Stable Two-Component Entropic Complexity on Classical and Quantum Law Spaces</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-02-scale-stable-two-component-entropic-complexity-o-17785936</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-02-scale-stable-two-component-entropic-complexity-o-17785936</guid>
    <pubDate>Tue, 02 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>entropy transport</category>
    <category>complexity</category>
    <category>interface entropy rate</category>
    <category>data-processing equivalence</category>
    <category>blackwell equivalence</category>
    <category>metric gradient flows</category>
    <category>wasserstein gradient flow</category>
    <category>jko scheme</category>
    <category>kullback-leibler divergence</category>
    <category>bures-hk distance</category>
    <category>fibered bures-hk</category>
    <category>FBHK</category>
    <source url="https://doi.org/10.5281/zenodo.17785936">10.5281/zenodo.17785936</source>
    <description><![CDATA[
      The first component, the internal law–time complexity J_int , is defined as a pathwise sum of divergences between consecutive internal laws.
Preprint | DOI: 10.5281/zenodo.17785936
    ]]></description>
  </item>
  <item>
    <title>A Two-Component Entropic Complexity for Discrete-Time Theories</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-02-a-two-component-entropic-complexity-for-discrete-17784015</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-02-a-two-component-entropic-complexity-for-discrete-17784015</guid>
    <pubDate>Tue, 02 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>discrete-time stochastic dynamics</category>
    <category>temporal complexity</category>
    <category>interface complexity</category>
    <category>entropy rate</category>
    <category>relative entropy</category>
    <category>f-divergence</category>
    <category>markov chains</category>
    <category>non-equilibrium steady states</category>
    <category>coarse-graining</category>
    <category>path-space implementation</category>
    <category>data processing inequality</category>
    <category>stochastic thermodynamics</category>
    <source url="https://doi.org/10.5281/zenodo.17784015">10.5281/zenodo.17784015</source>
    <description><![CDATA[
      A theory is defined as a probability law on bi-infinite (or semi-infinite) symbol sequences, while an implementation is a Markovian dynamical system with hidden states and an observation map that reproduces the same boundary law.
Preprint | DOI: 10.5281/zenodo.17784015
    ]]></description>
  </item>
  <item>
    <title>Internal Equilibria on Formal Concept Lattices in Finite No--Meta Law Spaces</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-12-01-internal-equilibria-on-formal-concept-lattices-i-17773600</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-12-01-internal-equilibria-on-formal-concept-lattices-i-17773600</guid>
    <pubDate>Mon, 01 Dec 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>no-meta</category>
    <category>formal concept analysis</category>
    <category>concept lattices</category>
    <category>tarski fixed point</category>
    <category>dynamical laws</category>
    <category>internal equilibria</category>
    <category>structural invariants</category>
    <category>information dimension</category>
    <category>monotone operators</category>
    <category>profile equivalence</category>
    <category>quotient context</category>
    <category>computational complexity</category>
    <source url="https://doi.org/10.5281/zenodo.17773600">10.5281/zenodo.17773600</source>
    <description><![CDATA[
      Each law–observer pair is equipped with internal structural scalars, such as intrinsic (state) dimension, visible dimension, visibility gap, and computational cost.
Preprint | DOI: 10.5281/zenodo.17773600
    ]]></description>
  </item>
  <item>
    <title>Information--Dimensional Law Selection under No--Meta Constraints</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-30-information-dimensional-law-selection-under-no-m-17769061</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-30-information-dimensional-law-selection-under-no-m-17769061</guid>
    <pubDate>Sun, 30 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>information dimension</category>
    <category>entropy dimension</category>
    <category>kolmogorov-sinai entropy</category>
    <category>symbolic dynamics</category>
    <category>law selection</category>
    <category>internal objective</category>
    <category>observer-dependent structure</category>
    <category>visibility gap</category>
    <category>complexity regularization</category>
    <category>description complexity</category>
    <category>multiplicative weights update</category>
    <category>law space optimization</category>
    <source url="https://doi.org/10.5281/zenodo.17769061">10.5281/zenodo.17769061</source>
    <description><![CDATA[
      For each law T, we extract structural scalars: a state information dimension d_state(T), observer-specific visible dimensions d_obs_i(T), nonnegative visibility gaps Gap_i(T)=d_state(T)-d_obs_i(T), and an abstract law complexity Comp(T).
Preprint | DOI: 10.5281/zenodo.17769061
    ]]></description>
  </item>
  <item>
    <title>Persistence-First Law--Space Exponents and Quantum Advantage over PFHS--TRoT--Blum Law--Time Semigroups</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-28-persistence-first-law-space-exponents-and-quantu-17748308</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-28-persistence-first-law-space-exponents-and-quantu-17748308</guid>
    <pubDate>Fri, 28 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>gradient flow</category>
    <category>information theory</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>law-time semigroups</category>
    <category>blum complexity</category>
    <category>implementation-independent complexity</category>
    <category>law-space exponents</category>
    <category>quantum advantage</category>
    <category>grover search</category>
    <source url="https://doi.org/10.5281/zenodo.17748308">10.5281/zenodo.17748308</source>
    <description><![CDATA[
      Building on persistence-first holographic systems (PFHS), fibered Bures–HK entropy–transport geometry (FBHK) and holographic observation quotients (HOQ), the paper defines PFHS–compatible law-time cost increments and a Blum-type complexity measure that track transport action, persistence change and HOQ gap along law-time trajectories.
Preprint | DOI: 10.5281/zenodo.17748308
    ]]></description>
  </item>
  <item>
    <title>An Implementation--Ready PFHS--TRoT--Blum Bootloader for Stable, Self--Improving Superintelligent Architectures</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-28-an-implementation-ready-pfhs-trot-blum-bootloade-17745065</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-28-an-implementation-ready-pfhs-trot-blum-bootloade-17745065</guid>
    <pubDate>Fri, 28 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>superintelligence</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>fibered bures-hk geometry</category>
    <category>FBHK</category>
    <category>holographic observation quotients</category>
    <category>HOQ</category>
    <category>gradient flows</category>
    <category>self-improving AI</category>
    <category>superintelligent architectures</category>
    <category>no-meta governance</category>
    <source url="https://doi.org/10.5281/zenodo.17745065">10.5281/zenodo.17745065</source>
    <description><![CDATA[
      It compresses a large corpus of prior work on Persistence-First Holographic Systems (PFHS), Fibered Bures–HK (FBHK) entropy–transport geometry, Holographic Observation Quotients (HOQ), value-anchored natural-law gradient flows, no-meta Theory of Relativity of Theories (TRoT), and PFHS–HOQ Blum-type device-independent complexity into a single YAML-based specification that can be directly consumed by human engineers and large language models.
Preprint | DOI: 10.5281/zenodo.17745065
    ]]></description>
  </item>
  <item>
    <title>Blum--Type Device--Independent Complexity over Law--Time Semigroups with PFHS--HOQ Structures</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-28-blum-type-device-independent-complexity-over-law-17744509</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-28-blum-type-device-independent-complexity-over-law-17744509</guid>
    <pubDate>Fri, 28 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>information theory</category>
    <category>computer science</category>
    <category>blum complexity</category>
    <category>blum measures</category>
    <category>device independent complexity</category>
    <category>generalised complexity theory</category>
    <category>law time semigroups</category>
    <category>computable dynamical systems</category>
    <category>computable analysis</category>
    <category>semantic cost models</category>
    <source url="https://doi.org/10.5281/zenodo.17744509">10.5281/zenodo.17744509</source>
    <description><![CDATA[
      We develop a machine–independent complexity theory for programs realised as trajectories of “law–time semigroups” on computable metric spaces.
Preprint | DOI: 10.5281/zenodo.17744509
    ]]></description>
  </item>
  <item>
    <title>Dynamic TRoT Fields and No-Meta Self-Relational Evaluation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-27-dynamic-trot-fields-and-no-meta-self-relational--17732875</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-27-dynamic-trot-fields-and-no-meta-self-relational--17732875</guid>
    <pubDate>Thu, 27 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>machine learning</category>
    <category>AI alignment</category>
    <category>AI safety</category>
    <category>superintelligence</category>
    <category>AI governance</category>
    <category>no-meta evaluation</category>
    <category>theory of relativity of theories</category>
    <category>trot</category>
    <category>theory fields</category>
    <source url="https://doi.org/10.5281/zenodo.17732875">10.5281/zenodo.17732875</source>
    <description><![CDATA[
      Instead of a single global theory catalogue, each location or agent in a PFHS/Post-FBHK universe carries a local catalogue of effective theories and a probability distribution over them.
Preprint | DOI: 10.5281/zenodo.17732875
    ]]></description>
  </item>
  <item>
    <title>A No-Meta Theory of Relativity of Theories</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-27-a-no-meta-theory-of-relativity-of-theories-17731000</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-27-a-no-meta-theory-of-relativity-of-theories-17731000</guid>
    <pubDate>Thu, 27 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>multi-agent systems</category>
    <category>theory of relativity of theories</category>
    <category>persistence-first</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>fibered bures-hk entropy-transport</category>
    <category>FBHK</category>
    <category>hellinger-kantorovich distance</category>
    <source url="https://doi.org/10.5281/zenodo.17731000">10.5281/zenodo.17731000</source>
    <description><![CDATA[
      Instead of treating evaluators, meta-learners and model selectors as external oracles, the paper embeds them as internal natural laws in the same entropy–transport background as the systems they assess.
Preprint | DOI: 10.5281/zenodo.17731000
    ]]></description>
  </item>
  <item>
    <title>Joint Contraction and ISS for Value-Anchored Natural-Law Gradient Flows</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-27-joint-contraction-and-iss-for-value-anchored-nat-17728994</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-27-joint-contraction-and-iss-for-value-anchored-nat-17728994</guid>
    <pubDate>Thu, 27 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>machine learning</category>
    <category>machine learning/ethics</category>
    <category>multi-agent systems</category>
    <category>gradient flows</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>fibered bures-hk</category>
    <source url="https://doi.org/10.5281/zenodo.17728994">10.5281/zenodo.17728994</source>
    <description><![CDATA[
      The model combines (i) law-level gradient flows on FBHK/Post-FBHK entropy–transport spaces, (ii) parameter-level gradient descent for value-anchored self-improvement, and (iii) defect-level gradient flows for multi-agent consistency and self-purification, together with slowly varying anchors and environments.
Preprint | DOI: 10.5281/zenodo.17728994
    ]]></description>
  </item>
  <item>
    <title>Consistency-Defect Gradient Flows and No-Meta Self-Purification in Value-Anchored Multi-Agent Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-26-consistency-defect-gradient-flows-and-no-meta-se-17724629</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-26-consistency-defect-gradient-flows-and-no-meta-se-17724629</guid>
    <pubDate>Wed, 26 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>multi-agents</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>geometry</category>
    <category>entropy-transport geometry</category>
    <category>hellinger-kantorovich distance</category>
    <category>bures-hk metric</category>
    <category>evolution variational inequality</category>
    <category>evi</category>
    <source url="https://doi.org/10.5281/zenodo.17724629">10.5281/zenodo.17724629</source>
    <description><![CDATA[
      The starting point is an analytic background where macroscopic dynamics of laws on a Polish state space are described by evolution variational inequality (EVI) gradient flows with respect to ET distances such as the Hellinger–Kantorovich and fibered Bures–HK metrics.
Preprint | DOI: 10.5281/zenodo.17724629
    ]]></description>
  </item>
  <item>
    <title>Stable Self-Improving AI under Value-Anchored Natural-Law Gradient Flows</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-26-stable-self-improving-ai-under-value-anchored-na-17718314</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-26-stable-self-improving-ai-under-value-anchored-na-17718314</guid>
    <pubDate>Wed, 26 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>mathematical model</category>
    <category>AI</category>
    <category>self-improving AI</category>
    <category>AI alignment</category>
    <category>value alignment</category>
    <category>gradient flows</category>
    <category>value-anchored potential</category>
    <category>natural-law specification</category>
    <category>markov kernel stability</category>
    <source url="https://doi.org/10.5281/zenodo.17718314">10.5281/zenodo.17718314</source>
    <description><![CDATA[
      The design space is the Wasserstein space P2(Theta) over a metric hypothesis space (Theta, d_Theta), equipped with a value-shortfall functional Val*(mu) = integral V(theta) mu(dtheta) that aggregates deficits in alignment, performance, or physical feasibility.
Preprint | DOI: 10.5281/zenodo.17718314
    ]]></description>
  </item>
  <item>
    <title>Value-Anchored Natural-Law Fronts over Reversible Persistence-First Holographic Systems II</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-25-value-anchored-natural-law-fronts-over-reversibl-17712716</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-25-value-anchored-natural-law-fronts-over-reversibl-17712716</guid>
    <pubDate>Tue, 25 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>mathematical model</category>
    <category>geometry</category>
    <category>value-anchored natural-law fronts</category>
    <category>entropy-transport</category>
    <category>hellinger-kantorovich distance</category>
    <category>wasserstein gradient flows</category>
    <category>scaling laws</category>
    <category>AI</category>
    <category>compute-optimal AI</category>
    <category>FBHK geometry</category>
    <source url="https://doi.org/10.5281/zenodo.17712716">10.5281/zenodo.17712716</source>
    <description><![CDATA[
      This preprint develops a value-anchored geometric framework on spaces of natural-law and scaling-law theories rather than proposing a single scaling law. It models distributions over theories with entropy-transport geometry and derives gradient-flow dynamics for selecting theory families under explicit value criteria.
Preprint | DOI: 10.5281/zenodo.17712716
    ]]></description>
  </item>
  <item>
    <title>Value-Anchored Natural-Law Fronts over Reversible Persistence-First Holographic Systems I</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-25-value-anchored-natural-law-fronts-over-reversibl-17707344</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-25-value-anchored-natural-law-fronts-over-reversibl-17707344</guid>
    <pubDate>Tue, 25 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>KPP</category>
    <category>mathematical model</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>geometry</category>
    <category>wasserstein geometry</category>
    <category>reversible markov chains</category>
    <category>persistence functional</category>
    <category>poisson equation</category>
    <source url="https://doi.org/10.5281/zenodo.17707344">10.5281/zenodo.17707344</source>
    <description><![CDATA[
      Starting from an EVI gradient flow of a total entropy functional on a fibered Bures–HK entropy–transport space, represented by a reversible Markov kernel with a unique invariant “origin law”, the paper introduces value-anchored natural-law fields that are intrinsically tied to the same dynamics.
Preprint | DOI: 10.5281/zenodo.17707344
    ]]></description>
  </item>
  <item>
    <title>Reversible Persistence-First Holographic Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-25-reversible-persistence-first-holographic-systems-17706175</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-25-reversible-persistence-first-holographic-systems-17706175</guid>
    <pubDate>Tue, 25 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>gradient flows</category>
    <category>mathematical model</category>
    <category>information theory</category>
    <category>PFHS</category>
    <category>persistence-first holographic systems</category>
    <category>geometry</category>
    <category>hellinger-kantorovich distance</category>
    <category>bures metric</category>
    <category>entropy-transport</category>
    <source url="https://doi.org/10.5281/zenodo.17706175">10.5281/zenodo.17706175</source>
    <description><![CDATA[
      Instead of using PDEs as primitives, the paper works in the metric–measure framework of EVI (evolution variational inequality) gradient flows on the Wasserstein space of probability laws.
Preprint | DOI: 10.5281/zenodo.17706175
    ]]></description>
  </item>
  <item>
    <title>Infinite Hierarchical Holographic Observation Quotients</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-23-infinite-hierarchical-holographic-observation-qu-17684539</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-23-infinite-hierarchical-holographic-observation-qu-17684539</guid>
    <pubDate>Sun, 23 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>gradient flows</category>
    <category>holographic observation quotient</category>
    <category>entropy-transport</category>
    <category>hellinger-kantorovich</category>
    <category>bures metric</category>
    <category>adaptive hierarchical box complexity</category>
    <category>information theory</category>
    <category>AI</category>
    <category>assouad-type dimensions</category>
    <category>jko scheme</category>
    <source url="https://doi.org/10.5281/zenodo.17684539">10.5281/zenodo.17684539</source>
    <description><![CDATA[
      Mathematically, the core results are modest but explicit: (i) stability of EVI (Evolution Variational Inequality) gradient flows under a truncated ℓ² metric on countable products and inverse limits, (ii) a design-oriented notion of adaptive hierarchical box complexity whose exponent collapses to 0 under mild, uniform small-scale assumptions, and (iii) a depth-independent compute bound for JKO-type numerical implementations when per-level costs form a summable sequence.
Preprint | DOI: 10.5281/zenodo.17684539
    ]]></description>
  </item>
  <item>
    <title>Post--FBHK Fibered Entropy--Transport Geometry with Petz Fibers and Type~III Persistence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-22-post-fbhk-fibered-entropy-transport-geometry-wit-17679426</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-22-post-fbhk-fibered-entropy-transport-geometry-wit-17679426</guid>
    <pubDate>Sat, 22 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>entropy-transport</category>
    <category>hellinger-kantorovich</category>
    <category>optimal transport</category>
    <category>geometry</category>
    <category>benamou-brenier formula</category>
    <category>hamilton-jacobi duality</category>
    <category>dirac reduction</category>
    <category>petz monotone metrics</category>
    <category>information geometry</category>
    <category>araki relative entropy</category>
    <source url="https://doi.org/10.5281/zenodo.17679426">10.5281/zenodo.17679426</source>
    <description><![CDATA[
      A central result is quarter rigidity: the Benamou-Brenier action with kinetic terms |v_t|^2 + kappa |w_t|^2 matches d_FET^2 if and only if the reaction coefficient = 1/4, fixing the canonical normalization uniquely through Dirac calibrations.
Preprint | DOI: 10.5281/zenodo.17679426
    ]]></description>
  </item>
  <item>
    <title>Self-Referential Persistent Modes in Human--AI Ecosystems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-21-self-referential-persistent-modes-in-human-ai-ec-17669224</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-21-self-referential-persistent-modes-in-human-ai-ec-17669224</guid>
    <pubDate>Fri, 21 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>category theory</category>
    <category>human-AI ecosystems</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>reflective subcategory</category>
    <category>fractal interface</category>
    <category>autopoietic interface</category>
    <source url="https://doi.org/10.5281/zenodo.17669224">10.5281/zenodo.17669224</source>
    <description><![CDATA[
      We focus on datacenter-scale AI services—such as large language model (LLM) deployments—together with the human populations that interact with them, and ask when such coupled infrastructures can support long-lived, structured environmental modes that are stabilized by their own interaction patterns.
Preprint | DOI: 10.5281/zenodo.17669224
    ]]></description>
  </item>
  <item>
    <title>Finsler Spacetime, Entropy--Transport Gradient Flows, and Fibered Bures--HK Geometry: From Relativistic Kinetic Gases to Persistence-First Holographic Universes</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-20-finsler-spacetime-entropy-transport-gradient-flo-17658411</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-20-finsler-spacetime-entropy-transport-gradient-flo-17658411</guid>
    <pubDate>Thu, 20 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>physics</category>
    <category>mathematical physics</category>
    <category>physical cosmology</category>
    <category>finsler spacetime</category>
    <category>lorentz-finsler geometry</category>
    <category>finsler-friedmann equation</category>
    <category>relativistic kinetic gas</category>
    <category>entropy-transport</category>
    <category>hellinger-kantorovich</category>
    <category>wasserstein-fisher-rao</category>
    <source url="https://doi.org/10.5281/zenodo.17658411">10.5281/zenodo.17658411</source>
    <description><![CDATA[
      Using Hellinger–Kantorovich (HK) / Wasserstein–Fisher–Rao type distances, it realises Finsler–Friedmann cosmological expansion as an EVI (Evolution Variational Inequality) gradient flow of a free-energy functional on a Finsler–HK configuration space.
Preprint | DOI: 10.5281/zenodo.17658411
    ]]></description>
  </item>
  <item>
    <title>Implementation--Ready Persistence-First Holographic Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-19-implementation-ready-persistence-first-holograph-17645180</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-19-implementation-ready-persistence-first-holograph-17645180</guid>
    <pubDate>Wed, 19 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>information theory</category>
    <category>persistence-first holographic systems</category>
    <category>PFHS</category>
    <category>gradient flows</category>
    <category>jordan-kinderlehrer-otto</category>
    <category>jko</category>
    <category>optimal transport</category>
    <category>category theory</category>
    <category>hellinger-kantorovich geometry</category>
    <category>finite markov chains</category>
    <source url="https://doi.org/10.5281/zenodo.17645180">10.5281/zenodo.17645180</source>
    <description><![CDATA[
      On the analytic side, the work assumes standard theory for gradient flows in metric spaces and the convergence of Jordan–Kinderlehrer–Otto (JKO) type minimizing–movement schemes (Ambrosio–Gigli–Savaré, Jordan–Kinderlehrer–Otto, Liero–Mielke–Savaré, Maas, Mielke, Carlen–Maas).
Preprint | DOI: 10.5281/zenodo.17645180
    ]]></description>
  </item>
  <item>
    <title>Persistence-First Holographic Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-18-persistence-first-holographic-systems-17636648</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-18-persistence-first-holographic-systems-17636648</guid>
    <pubDate>Tue, 18 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>geometry</category>
    <category>category theory</category>
    <category>entropy-transport geometry</category>
    <category>hellinger-kantorovich distance</category>
    <category>gradient flows</category>
    <category>multiscale dissipative systems</category>
    <category>persistence monoids</category>
    <category>categorical open systems</category>
    <category>holographic boundary structures</category>
    <category>finite markov chains</category>
    <category>quantum markov semigroups</category>
    <category>bures-hk metrics</category>
    <source url="https://doi.org/10.5281/zenodo.17636648">10.5281/zenodo.17636648</source>
    <description><![CDATA[
      The paper assumes the standard existence, uniqueness, and contractivity theory for gradient flows in classical, discrete, and quantum settings (Ambrosio-Gigli-Savare, Liero-Mielke-Savare, Maas, Erbar-Maas, Mielke, Carlen-Maas) and asks how ET gradient systems on a multiscale world-plus-boundary architecture can be packaged so that persistence, self-like structure, and curvature control become transparent.
Preprint | DOI: 10.5281/zenodo.17636648
    ]]></description>
  </item>
  <item>
    <title>Holographic Observation Quotients and Fractal Boundaries: A Model-Agnostic Design Theory for Compute-Optimal Learning</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-13-holographic-observation-quotients-and-fractal-bo-17601860</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-13-holographic-observation-quotients-and-fractal-bo-17601860</guid>
    <pubDate>Thu, 13 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>machine learning</category>
    <category>large language models</category>
    <category>scaling laws</category>
    <category>compute-performance</category>
    <category>evi</category>
    <category>gradient flows</category>
    <category>fractals</category>
    <category>observation quotients</category>
    <category>holographic</category>
    <category>holographic compute law</category>
    <source url="https://doi.org/10.5281/zenodo.17601860">10.5281/zenodo.17601860</source>
    <description><![CDATA[
      On the bulk side, the theory assumes an EVI gradient flow of an energy functional on P(X) and a Lipschitz performance functional whose near-optimal sublevel sets have finite Minkowski dimension.
Preprint | DOI: 10.5281/zenodo.17601860
    ]]></description>
  </item>
  <item>
    <title>Persistence-First Natural Laws for Benevolent Propagation</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-13-persistence-first-natural-laws-for-benevolent-pr-17602030</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-13-persistence-first-natural-laws-for-benevolent-pr-17602030</guid>
    <pubDate>Thu, 13 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>superintelligence</category>
    <category>persistence-first</category>
    <category>AI ethics</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>benevolent AI</category>
    <category>natural laws</category>
    <category>gradient flows</category>
    <source url="https://doi.org/10.5281/zenodo.17602030">10.5281/zenodo.17602030</source>
    <description><![CDATA[
      Instead of postulating utility functions, value alignment, or externally chosen objectives, the paper takes only persistence under finite resources as a primitive order on ensembles of processes, and builds all higher structure from this single assumption.
Preprint | DOI: 10.5281/zenodo.17602030
    ]]></description>
  </item>
  <item>
    <title>Gradient-Flow-Based Compute--Performance Trade-offs for Intelligent Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-13-gradient-flow-based-compute-performance-trade-of-17596361</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-13-gradient-flow-based-compute-performance-trade-of-17596361</guid>
    <pubDate>Thu, 13 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>machine learning</category>
    <category>large language models</category>
    <category>gradient flows</category>
    <category>evi</category>
    <category>observation quotients</category>
    <category>scaling laws</category>
    <category>preimage minkowski dimension</category>
    <category>residual networks</category>
    <category>jko scheme</category>
    <source url="https://doi.org/10.5281/zenodo.17596361">10.5281/zenodo.17596361</source>
    <description><![CDATA[
      Under a “gradient-flow universal intelligence process (UIP)” hypothesis, the work isolates structural mechanisms that constrain how far a given architecture can push performance under finite compute, rather than proposing another empirical scaling law.
Preprint | DOI: 10.5281/zenodo.17596361
    ]]></description>
  </item>
  <item>
    <title>Compute-Optimal AI via Image--EVI, Interior Bures--HK Control, and Fractal Dendritic Approximation (DIR)</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-10-compute-optimal-ai-via-image-evi-interior-bures--17576546</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-10-compute-optimal-ai-via-image-evi-interior-bures--17576546</guid>
    <pubDate>Mon, 10 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>geometry</category>
    <category>information theory</category>
    <category>compute reduction</category>
    <category>scaling laws</category>
    <category>entropy-transport</category>
    <category>hellinger-kantorovich</category>
    <source url="https://doi.org/10.5281/zenodo.17576546">10.5281/zenodo.17576546</source>
    <description><![CDATA[
      Here alpha and beta are the empirical scaling exponents for parameters and tokens, is a robust image Lipschitz proxy, and (eta, rho) encode slack from acceptance tests.
Preprint | DOI: 10.5281/zenodo.17576546
    ]]></description>
  </item>
  <item>
    <title>Natural Language as Preimage, Formal Semantics as Image</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-07-natural-language-as-preimage-formal-semantics-as-17547803</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-07-natural-language-as-preimage-formal-semantics-as-17547803</guid>
    <pubDate>Fri, 07 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>language</category>
    <category>category theory</category>
    <category>enriched categories</category>
    <category>kan extension</category>
    <category>cech nerve</category>
    <category>natural language to constraints</category>
    <source url="https://doi.org/10.5281/zenodo.17547803">10.5281/zenodo.17547803</source>
    <description><![CDATA[
      The bridge is right-written with composition expressed as g after f and is Sup-enriched, enabling explicit bookkeeping of strong vs (op)lax transport with falsifiable audit tags.
Preprint | DOI: 10.5281/zenodo.17547803
    ]]></description>
  </item>
  <item>
    <title>Observation Quotients and Learning-as-Lifting</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-06-observation-quotients-and-learning-as-lifting-17539800</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-06-observation-quotients-and-learning-as-lifting-17539800</guid>
    <pubDate>Thu, 06 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>geometry</category>
    <category>information theory</category>
    <category>optimal transport</category>
    <category>machine learning</category>
    <category>evi</category>
    <category>jko</category>
    <source url="https://doi.org/10.5281/zenodo.17539800">10.5281/zenodo.17539800</source>
    <description><![CDATA[
      On probability measures, we study the inf-projection G of an energy F along an observation map O and prove an image-EVI result: lambda-EVI gradient flows of F on (P2(X), W2) push forward to relaxed or exact lambda-EVI flows of G on (P2(Z), W2).
Preprint | DOI: 10.5281/zenodo.17539800
    ]]></description>
  </item>
  <item>
    <title>Image--EVI on Metric Quotients for Gradient Flows</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-04-image-evi-on-metric-quotients-for-gradient-flows-17518572</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-04-image-evi-on-metric-quotients-for-gradient-flows-17518572</guid>
    <pubDate>Tue, 04 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>AI</category>
    <category>image-evi</category>
    <category>metric quotient</category>
    <category>image pseudometric</category>
    <category>gradient flows</category>
    <category>evi gradient flow</category>
    <category>fractional strang splitting</category>
    <category>analytic semigroups</category>
    <category>hilbert projective metric</category>
    <category>operator scaling</category>
    <source url="https://doi.org/10.5281/zenodo.17518572">10.5281/zenodo.17518572</source>
    <description><![CDATA[
      The paper develops a rigorous pathway from geometry to implementation audits and to potential application templates for large language models (LLMs).
Preprint | DOI: 10.5281/zenodo.17518572
    ]]></description>
  </item>
  <item>
    <title>A Model-Agnostic, Performance-Pushforward Theory of Scaling Laws</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-11-04-a-model-agnostic-performance-pushforward-theory--17520859</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-11-04-a-model-agnostic-performance-pushforward-theory--17520859</guid>
    <pubDate>Tue, 04 Nov 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>AI</category>
    <category>machine learning</category>
    <category>optimization</category>
    <category>information theory</category>
    <category>numerical analysis</category>
    <category>computer science</category>
    <category>scaling laws</category>
    <category>gradient flows</category>
    <category>ambrosio-gigli-savaré</category>
    <category>evi</category>
    <source url="https://doi.org/10.5281/zenodo.17520859">10.5281/zenodo.17520859</source>
    <description><![CDATA[
      The central idea is to view performance as the pushforward of an EVI λ gradient flow under a Lipschitz evaluation map, while scale is measured by the geometry of preimages of performance targets.
Preprint | DOI: 10.5281/zenodo.17520859
    ]]></description>
  </item>
  <item>
    <title>Fibered Bures--HK Entropy--Transport</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-30-fibered-bures-hk-entropy-transport-17483082</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-30-fibered-bures-hk-entropy-transport-17483082</guid>
    <pubDate>Thu, 30 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>geometry</category>
    <category>hellinger-kantorovich</category>
    <category>wasserstein-fisher-rao</category>
    <category>optimal transport</category>
    <category>entropy transport</category>
    <category>benamou-brenier</category>
    <category>reaction-diffusion</category>
    <category>KL divergence</category>
    <category>relative entropy</category>
    <source url="https://doi.org/10.5281/zenodo.17483082">10.5281/zenodo.17483082</source>
    <description><![CDATA[
      We prove dynamic–static equivalence for the hybrid ET functional and identify the unique reaction coefficient 1/4 via convex duality with endpoint Kullback–Leibler (KL) terms.
Preprint | DOI: 10.5281/zenodo.17483082
    ]]></description>
  </item>
  <item>
    <title>Right-Written, Semantics-Admissible Process Foundations</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-29-right-written-semantics-admissible-process-found-17469937</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-29-right-written-semantics-admissible-process-found-17469937</guid>
    <pubDate>Wed, 29 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>right-written composition</category>
    <category>category theory</category>
    <category>profunctor</category>
    <category>monoidal nucleus</category>
    <category>evaluator calculus</category>
    <category>KPP front speed</category>
    <category>graphblas</category>
    <category>swarm intelligence</category>
    <category>collective intelligence</category>
    <source url="https://doi.org/10.5281/zenodo.17469937">10.5281/zenodo.17469937</source>
    <description><![CDATA[
      Arrays are treated as QQ Q -enriched profunctors with convolution ; associativity and unitality are characterized via declared-join Fubini / (weak) Beck–Chevalley under a two-tier axiom system (W/S).
Preprint | DOI: 10.5281/zenodo.17469937
    ]]></description>
  </item>
  <item>
    <title>JOSNL Corpus: Final Scientific Integration</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-24-josnl-corpus-final-scientific-integration-17429908</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-24-josnl-corpus-final-scientific-integration-17429908</guid>
    <pubDate>Fri, 24 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>machine learning</category>
    <category>anytime-valid testing</category>
    <category>network interference</category>
    <category>randomization inference</category>
    <category>spectral bound</category>
    <category>meta-analysis</category>
    <category>JOSNL</category>
    <source url="https://doi.org/10.5281/zenodo.17429908">10.5281/zenodo.17429908</source>
    <description><![CDATA[
      The work is designed to satisfy four scientific requirements simultaneously: observability , identifiability under network interference , anytime-valid testing , and reproducibility.
Preprint | DOI: 10.5281/zenodo.17429908
    ]]></description>
  </item>
  <item>
    <title>Inference in Normal Form: Unifying LLM Tricks via TRoT</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-19-inference-in-normal-form-unifying-llm-tricks-via-17389109</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-19-inference-in-normal-form-unifying-llm-tricks-via-17389109</guid>
    <pubDate>Sun, 19 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>AI</category>
    <category>llm inference</category>
    <category>machine learning</category>
    <category>decoding</category>
    <category>mbr</category>
    <category>conformal prediction</category>
    <category>verifier</category>
    <category>rag</category>
    <category>chain-of-thought</category>
    <category>tree-of-thought</category>
    <source url="https://doi.org/10.5281/zenodo.17389109">10.5281/zenodo.17389109</source>
    <description><![CDATA[
      Our formulation uses enriched category theory over the Lawvere cost quantale (tropical (min,+) semiring): left/right Kan extensions / / / , residuation (elementwise residuals), masking and nuclei (1-Lipschitz projectors).
Preprint | DOI: 10.5281/zenodo.17389109
    ]]></description>
  </item>
  <item>
    <title>Practical Theory of Relativity of Theories - RAVE</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-16-practical-theory-of-relativity-of-theories-rave-17364444</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-16-practical-theory-of-relativity-of-theories-rave-17364444</guid>
    <pubDate>Thu, 16 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>machine learning</category>
    <category>large language models</category>
    <category>algorithms</category>
    <category>category theory</category>
    <category>supermartingale</category>
    <category>evi/jko</category>
    <category>graphblas</category>
    <category>eudaemonia</category>
    <category>dobrushin</category>
    <source url="https://doi.org/10.5281/zenodo.17364444">10.5281/zenodo.17364444</source>
    <description><![CDATA[
      This preprint defines RAVE, a no-meta auditing protocol in which humans and AI systems evaluate one another using anytime-valid tests, peer-prediction rules, and representation-independent comparison geometry. It focuses on verifiable relative evaluation without relying on a privileged external judge.
Preprint | DOI: 10.5281/zenodo.17364444
    ]]></description>
  </item>
  <item>
    <title>Theory of Relativity of Theories</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-14-theory-of-relativity-of-theories-17345898</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-14-theory-of-relativity-of-theories-17345898</guid>
    <pubDate>Tue, 14 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>categorical semantics</category>
    <category>adjunction</category>
    <category>galois connection</category>
    <category>polarity</category>
    <category>residuation</category>
    <category>residuated lattice</category>
    <category>quantale</category>
    <category>enrichment</category>
    <category>monoidal closed category</category>
    <source url="https://doi.org/10.5281/zenodo.17345898">10.5281/zenodo.17345898</source>
    <description><![CDATA[
      We organize proof systems and models through polarity (Galois connections/adjunctions) and residuation, and study the role of lax/oplax morphisms in transporting theorems between theories.
Preprint | DOI: 10.5281/zenodo.17345898
    ]]></description>
  </item>
  <item>
    <title>Practical Theory of Relativity of Theories (TRoT)</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-14-practical-theory-of-relativity-of-theories-trot-17349720</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-14-practical-theory-of-relativity-of-theories-trot-17349720</guid>
    <pubDate>Tue, 14 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>theory alignment</category>
    <category>category theory</category>
    <category>profunctor</category>
    <category>distributor</category>
    <category>quantale</category>
    <category>residuation</category>
    <category>large language models</category>
    <category>AI</category>
    <category>adjunction</category>
    <category>kan extension</category>
    <category>isbell conjugacy</category>
    <source url="https://doi.org/10.5281/zenodo.17349720">10.5281/zenodo.17349720</source>
    <description><![CDATA[
      It presents a right-written profunctor framework over ν-quantales in which Left Kan implements generation and Right Kan implements safety/verification , linked by readable adjunction (Galois) laws and an Isbell round-trip distortion metric.
Preprint | DOI: 10.5281/zenodo.17349720
    ]]></description>
  </item>
  <item>
    <title>Right-Written Composition Foundations for Comparative Universes</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-12-right-written-composition-foundations-for-compar-17334218</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-12-right-written-composition-foundations-for-compar-17334218</guid>
    <pubDate>Sun, 12 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>multi agents</category>
    <category>large language models</category>
    <category>AI alignment</category>
    <category>quantaloid</category>
    <category>quantale</category>
    <category>category theory</category>
    <category>sup-enriched category</category>
    <category>right-written composition</category>
    <category>convolution</category>
    <category>kleene fixed point</category>
    <category>ω-cpo</category>
    <source url="https://doi.org/10.5281/zenodo.17334218">10.5281/zenodo.17334218</source>
    <description><![CDATA[
      This preprint develops a right-written compositional framework for comparing results across cost, probability, and relational settings without fixing a single evaluative basis. It formalizes reusable path, gluing, masking, and transport constructions for comparative mathematics.
Preprint | DOI: 10.5281/zenodo.17334218
    ]]></description>
  </item>
  <item>
    <title>Comparative Universes</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-11-comparative-universes-17317567</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-11-comparative-universes-17317567</guid>
    <pubDate>Sat, 11 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>enriched category theory</category>
    <category>quantaloid</category>
    <category>quantales</category>
    <category>double categories</category>
    <category>proarrow equipment</category>
    <category>čech gluing</category>
    <category>promonoidal weights</category>
    <category>weighted limits</category>
    <category>attenuation</category>
    <category>first-step masked bound</category>
    <category>non-dominance criterion</category>
    <source url="https://doi.org/10.5281/zenodo.17317567">10.5281/zenodo.17317567</source>
    <description><![CDATA[
      This preprint introduces a typed framework for comparing and composing mathematical universes through admissible translations and explicit comparison data. It studies local gluing, path aggregation, attenuation, and base-change rules in quantaloid-valued settings.
Preprint | DOI: 10.5281/zenodo.17317567
    ]]></description>
  </item>
  <item>
    <title>Self-Monitoring and Controllable Evolution of Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-10-self-monitoring-and-controllable-evolution-of-in-17309195</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-10-self-monitoring-and-controllable-evolution-of-in-17309195</guid>
    <pubDate>Fri, 10 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>intelligence</category>
    <category>category theory</category>
    <category>day convolution</category>
    <category>profunctor</category>
    <category>promonoidal distributor</category>
    <category>enriched category theory</category>
    <category>lawvere metric</category>
    <category>external pseudometric</category>
    <category>capability kernels</category>
    <category>filtered colimit</category>
    <category>levelwise cofiltered limit</category>
    <source url="https://doi.org/10.5281/zenodo.17309195">10.5281/zenodo.17309195</source>
    <description><![CDATA[
      Building on the Structured Flow across Scales (SFaS) bicompletion—filtered generation followed by UU U -small levelwise cofiltered selection—we induce (op)lax promonoidal kernels on the capability category from agent-side interaction and recognition profunctors, and carry out all Day convolutions in the functor category [Acapop,E][ , E] [ A cap op , E ].
Preprint | DOI: 10.5281/zenodo.17309195
    ]]></description>
  </item>
  <item>
    <title>Dynamic Fractal Category Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-09-dynamic-fractal-category-theory-17299070</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-09-dynamic-fractal-category-theory-17299070</guid>
    <pubDate>Thu, 09 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>fractals</category>
    <category>frobenius monad</category>
    <category>comonad</category>
    <category>strong monoidal action</category>
    <category>ind-pro bicompletion</category>
    <category>equivariant kan extension</category>
    <category>day convolution</category>
    <category>newman's lemma</category>
    <category>tamari lattice</category>
    <category>final functors</category>
    <category>restricted yoneda</category>
    <source url="https://doi.org/10.5281/zenodo.17299070">10.5281/zenodo.17299070</source>
    <description><![CDATA[
      We give a skeletal presentation and a left-associated normal form whose rewrite system terminates via a lexicographic measure refined by Tamari height and is locally confluent through a finite list of critical-pair shapes.
Preprint | DOI: 10.5281/zenodo.17299070
    ]]></description>
  </item>
  <item>
    <title>Structured Flow across Scales</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-09-structured-flow-across-scales-17304179</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-09-structured-flow-across-scales-17304179</guid>
    <pubDate>Thu, 09 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>strong monoidal action</category>
    <category>2-categories</category>
    <category>frobenius monads</category>
    <category>rewriting systems</category>
    <category>newman's lemma</category>
    <category>tamari lattice</category>
    <category>final functors</category>
    <category>ind/pro bicompletion</category>
    <category>presheaves</category>
    <category>day convolution</category>
    <category>kan extension</category>
    <source url="https://doi.org/10.5281/zenodo.17304179">10.5281/zenodo.17304179</source>
    <description><![CDATA[
      On the transport side we specify a strong monoidal 2-functorial action whose comparison data carry Frobenius (co)monad structure by transport and are independent of bracketing.
Preprint | DOI: 10.5281/zenodo.17304179
    ]]></description>
  </item>
  <item>
    <title>Fractal Category Theory</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-08-fractal-category-theory-17292137</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-08-fractal-category-theory-17292137</guid>
    <pubDate>Wed, 08 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>frobenius monad</category>
    <category>comonad</category>
    <category>ind-completion</category>
    <category>pro-completion</category>
    <category>ind-pro bicompletion</category>
    <category>kan extension</category>
    <category>day convolution</category>
    <category>lawvere metric</category>
    <category>algebraic compactness</category>
    <category>ambifixpoint</category>
    <category>equivariant functor</category>
    <source url="https://doi.org/10.5281/zenodo.17292137">10.5281/zenodo.17292137</source>
    <description><![CDATA[
      A mixed indexing category is used to show that bilimit computations reduce to a small subpresentation under accessibility and preservation assumptions, yielding presentation-independent formulas and a tight link between ind-pro bicompletion and a fraction-style construction.
Preprint | DOI: 10.5281/zenodo.17292137
    ]]></description>
  </item>
  <item>
    <title>Observation as Coarse-Graining</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-06-observation-as-coarse-graining-17274518</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-06-observation-as-coarse-graining-17274518</guid>
    <pubDate>Mon, 06 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>hellinger-kantorovich</category>
    <category>bures angle</category>
    <category>quantum fisher information</category>
    <category>entropy-transport</category>
    <category>optimal transport</category>
    <category>gradient flows</category>
    <category>jko scheme</category>
    <category>data processing inequality</category>
    <category>coarse-graining</category>
    <category>dynamic-static equivalence</category>
    <category>measurable selection</category>
    <category>cone-lift</category>
    <source url="https://doi.org/10.5281/zenodo.17274518">10.5281/zenodo.17274518</source>
    <description><![CDATA[
      The “law” sector evolves on the Hellinger–Kantorovich (HK) base (transport + reaction), while experimental readout lives on Bures/Quantum Fisher Information (QFI) fibers.
Preprint | DOI: 10.5281/zenodo.17274518
    ]]></description>
  </item>
  <item>
    <title>Nondual Dynamical Quantum Geometry</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-05-nondual-dynamical-quantum-geometry-17268502</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-05-nondual-dynamical-quantum-geometry-17268502</guid>
    <pubDate>Sun, 05 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>gravity theory</category>
    <category>quantum gravity theory</category>
    <category>nondual dynamical quantum geometry</category>
    <category>operational physical idealisation</category>
    <category>bures metric</category>
    <category>quantum fisher information</category>
    <category>hellinger-kantorovich distance</category>
    <category>entropy-transport</category>
    <category>optimal transport</category>
    <category>quantum markov semigroups</category>
    <category>lieb-robinson bounds</category>
    <category>quasi-locality</category>
    <source url="https://doi.org/10.5281/zenodo.17268502">10.5281/zenodo.17268502</source>
    <description><![CDATA[
      The law sector evolves on the unbalanced Hellinger–Kantorovich (HK) geometry, while the field sector evolves on fiber Bures geometry.
Preprint | DOI: 10.5281/zenodo.17268502
    ]]></description>
  </item>
  <item>
    <title>OPI Gauge Dynamics</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-05-opi-gauge-dynamics-17272609</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-05-opi-gauge-dynamics-17272609</guid>
    <pubDate>Sun, 05 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>hellinger-kantorovich</category>
    <category>unbalanced optimal transport</category>
    <category>bures angle</category>
    <category>sld-qfi</category>
    <category>choi states</category>
    <category>jko scheme</category>
    <category>evolution variational inequality</category>
    <category>gkls</category>
    <category>lieb-robinson bounds</category>
    <category>total variation</category>
    <category>ring-down</category>
    <category>nondual modeling</category>
    <source url="https://doi.org/10.5281/zenodo.17272609">10.5281/zenodo.17272609</source>
    <description><![CDATA[
      The base geometry is defined by the Hellinger-Kantorovich (HK) minimum-action principle (continuity equation with reaction), while the static entropy-transport form and the two-point 4 delta^2 law are recovered as consequences.
Preprint | DOI: 10.5281/zenodo.17272609
    ]]></description>
  </item>
  <item>
    <title>Nondual Autopoietic Excitations</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-03-nondual-autopoietic-excitations-17254917</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-03-nondual-autopoietic-excitations-17254917</guid>
    <pubDate>Fri, 03 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>nonduality</category>
    <category>autopoiesis</category>
    <category>law selection</category>
    <category>cahn-hilliard</category>
    <category>allen-cahn</category>
    <category>relabeling symmetry</category>
    <category>gauge invariance</category>
    <category>eyring-kramers law</category>
    <category>metastability</category>
    <category>maxwell selection</category>
    <category>modica-mortola</category>
    <category>gammaγ-convergence</category>
    <source url="https://doi.org/10.5281/zenodo.17254917">10.5281/zenodo.17254917</source>
    <description><![CDATA[
      The key novelty is to evolve the “alphabet” of admissible laws on the Hellinger–Kantorovich (HK) geometry of unbalanced optimal transport, rather than using an ad hoc Wasserstein + Fisher–Rao split.
Preprint | DOI: 10.5281/zenodo.17254917
    ]]></description>
  </item>
  <item>
    <title>Unified Natural-Law Intelligence (UNLI)</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-02-unified-natural-law-intelligence-unli-17249352</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-02-unified-natural-law-intelligence-unli-17249352</guid>
    <pubDate>Thu, 02 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>asi</category>
    <category>superintelligence</category>
    <category>unified natural-law intelligence</category>
    <category>no-meta dialectical limit</category>
    <category>audited meta-dependence</category>
    <category>invariant-constraint selectors</category>
    <category>e-process</category>
    <category>test supermartingale</category>
    <category>ville inequality</category>
    <source url="https://doi.org/10.5281/zenodo.17249352">10.5281/zenodo.17249352</source>
    <description><![CDATA[
      The work proposes a physics-grounded theory of intelligence as a nondual autopoietic excitation governed by a global energy–dissipation inequality (EDI) and audited by anytime-valid statistics.
Preprint | DOI: 10.5281/zenodo.17249352
    ]]></description>
  </item>
  <item>
    <title>Nondual Autopoietic Excitations</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-10-01-nondual-autopoietic-excitations-17239149</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-10-01-nondual-autopoietic-excitations-17239149</guid>
    <pubDate>Wed, 01 Oct 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>nonduality</category>
    <category>autopoiesis</category>
    <category>law selection</category>
    <category>cahn-hilliard</category>
    <category>allen-cahn</category>
    <category>relabeling symmetry</category>
    <category>gauge invariance</category>
    <category>eyring-kramers law</category>
    <category>metastability</category>
    <category>maxwell selection</category>
    <category>modica-mortola</category>
    <category>gammaγ-convergence</category>
    <source url="https://doi.org/10.5281/zenodo.17239149">10.5281/zenodo.17239149</source>
    <description><![CDATA[
      The key novelty is to evolve the “alphabet” of admissible laws on the Hellinger–Kantorovich (HK) geometry of unbalanced optimal transport, rather than using an ad hoc Wasserstein + Fisher–Rao split.
Preprint | DOI: 10.5281/zenodo.17239149
    ]]></description>
  </item>
  <item>
    <title>PFAD under the Principle of Natural Scarcity</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-29-pfad-under-the-principle-of-natural-scarcity-17220983</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-29-pfad-under-the-principle-of-natural-scarcity-17220983</guid>
    <pubDate>Mon, 29 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>anytime-valid inference</category>
    <category>e-process</category>
    <category>ville inequality</category>
    <category>cumulant generating function</category>
    <category>cgf symmetrization</category>
    <category>PFAD</category>
    <source url="https://doi.org/10.5281/zenodo.17220983">10.5281/zenodo.17220983</source>
    <description><![CDATA[
      We introduce a transcendental frame in which bands (state/time bands) formalize where geometry, calibration, and anytime-valid auditing remain meaningful.
Preprint | DOI: 10.5281/zenodo.17220983
    ]]></description>
  </item>
  <item>
    <title>A Representation-Independent Natural-Law Field Theory for No-Meta, Audited Superintelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-29-a-representation-independent-natural-law-field-t-17223573</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-29-a-representation-independent-natural-law-field-t-17223573</guid>
    <pubDate>Mon, 29 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>machine learning</category>
    <category>field theory</category>
    <category>AI alignment</category>
    <category>no-meta</category>
    <category>representation independence</category>
    <category>audit-compatible kernel</category>
    <category>ac-kernel</category>
    <category>markov kernel</category>
    <source url="https://doi.org/10.5281/zenodo.17223573">10.5281/zenodo.17223573</source>
    <description><![CDATA[
      The core idea is to replace external objectives with physics-style invariants and verifiable audits: free-energy descent (GENERIC), anytime-valid testing (test supermartingales / e-values), transport via JKO/EVI, reaction–diffusion coexistence with Fisher–KPP speed floors, and gauge-curvature regularization.
Preprint | DOI: 10.5281/zenodo.17223573
    ]]></description>
  </item>
  <item>
    <title>Persistence-First Emergence of Relational Benevolence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-28-persistence-first-emergence-of-relational-benevo-17217036</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-28-persistence-first-emergence-of-relational-benevo-17217036</guid>
    <pubDate>Sun, 28 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>superintelligence</category>
    <category>AI alignment</category>
    <category>ethics</category>
    <category>persistence-first</category>
    <category>emergence</category>
    <category>relational</category>
    <source url="https://doi.org/10.5281/zenodo.17217036">10.5281/zenodo.17217036</source>
    <description><![CDATA[
      A nondual bridge aligns audit and geometry: P1 (predictable signed error-bound) links audit improvement ΔhRB,t≤0 ,t 0 Δ h RB , t ≤ 0 to geometric descent ΔDt≤0 0 Δ D t ≤ 0.
Preprint | DOI: 10.5281/zenodo.17217036
    ]]></description>
  </item>
  <item>
    <title>Doctrine =&gt; Closure =&gt; Motion =&gt; Time: Portable Pure Theory of Non-Dual Harmony</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-26-doctrine-closure-motion-time-portable-pure-theor-17204755</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-26-doctrine-closure-motion-time-portable-pure-theor-17204755</guid>
    <pubDate>Fri, 26 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>kz doctrine</category>
    <category>scott closure</category>
    <category>lawvere metric</category>
    <category>continuous dcpo</category>
    <category>tarski fixed point</category>
    <category>nucleus</category>
    <category>firmly nonexpansive mapping</category>
    <category>metric projection</category>
    <category>fejér monotonicity</category>
    <source url="https://doi.org/10.5281/zenodo.17204755">10.5281/zenodo.17204755</source>
    <description><![CDATA[
      This paper presents a structural pipeline from doctrinal reflection to closure, motion, and internal time. It formalizes the construction on domains and metric models, proving fixed-point, nonexpansiveness, projection, and minimizing-movement results that make the dynamics portable across multiple mathematical settings.
Preprint | DOI: 10.5281/zenodo.17204755
    ]]></description>
  </item>
  <item>
    <title>Persistence as Closure: An Assumption-Transparent Modular Core for Motion and Internal Time</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-26-persistence-as-closure-an-assumption-transparent-17209556</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-26-persistence-as-closure-an-assumption-transparent-17209556</guid>
    <pubDate>Fri, 26 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>persistence</category>
    <category>persistence as closure</category>
    <category>fixed points</category>
    <category>minimizing movements</category>
    <category>generalized minimizing movement</category>
    <category>nonexpansive mappings</category>
    <category>internal time</category>
    <category>monotonicity</category>
    <category>opial property</category>
    <category>firmly nonexpansive</category>
    <category>convex analysis</category>
    <category>geometry</category>
    <source url="https://doi.org/10.5281/zenodo.17209556">10.5281/zenodo.17209556</source>
    <description><![CDATA[
      This article develops a portable core theory in which persistence is modeled as a closure operator and motion arises from minimizing-movement dynamics. It separates baseline results from optional assumption modules, derives an internal time from distance-to-closure decrease, and illustrates the framework with convex, lattice, and information-oriented examples.
Preprint | DOI: 10.5281/zenodo.17209556
    ]]></description>
  </item>
  <item>
    <title>A Natural-Law Theory of Fundamental Suffering</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-25-a-natural-law-theory-of-fundamental-suffering-17199498</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-25-a-natural-law-theory-of-fundamental-suffering-17199498</guid>
    <pubDate>Thu, 25 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>reaction-diffusion</category>
    <category>advection-diffusion-reaction</category>
    <category>hodge decomposition</category>
    <category>coexact circulation</category>
    <category>lyapunov floor</category>
    <category>KPP front speed</category>
    <category>principal eigenvalue</category>
    <category>suffering</category>
    <source url="https://doi.org/10.5281/zenodo.17199498">10.5281/zenodo.17199498</source>
    <description><![CDATA[
      The core mechanics couple reaction–advection–diffusion PDEs with Hodge projections, isolating coexact (circulation) flux as a gauge-invariant maintainer of persistent burden.
Preprint | DOI: 10.5281/zenodo.17199498
    ]]></description>
  </item>
  <item>
    <title>Audited Self-Improvement Loop for LLMs</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-24-audited-self-improvement-loop-for-llms-17188268</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-24-audited-self-improvement-loop-for-llms-17188268</guid>
    <pubDate>Wed, 24 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Article</category>
    <category>AI</category>
    <category>large language models</category>
    <category>superintelligence</category>
    <category>self-improving AI</category>
    <category>audited optimization</category>
    <category>e-process</category>
    <category>anytime-valid</category>
    <category>ville inequality</category>
    <category>catoni clipping</category>
    <category>sliding-window MGF</category>
    <category>dinkelbach</category>
    <source url="https://doi.org/10.5281/zenodo.17188268">10.5281/zenodo.17188268</source>
    <description><![CDATA[
      It combines anytime-valid e-process auditing (with Ville gate ), finite-window non-vacuity ( FW-1 ), heavy-tail guards (Catoni clipping + sliding-window MGF), sequentially wired e-gates inside Dinkelbach ratio optimization , FKPP/Kingman -style speed KPIs with censoring-aware block bootstrap, and information floors via winsorized Pearson |r| , HSIC , and distance correlation (dCor) with permutation tests and residualization.
Article | DOI: 10.5281/zenodo.17188268
    ]]></description>
  </item>
  <item>
    <title>Daily Explosive-Growth Protocol: Toward Free, Benevolent, and Safe Superintelligence without Meta Governance</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-24-daily-explosive-growth-protocol-toward-free-bene-17189422</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-24-daily-explosive-growth-protocol-toward-free-bene-17189422</guid>
    <pubDate>Wed, 24 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>self-improving AI</category>
    <category>superintelligence</category>
    <category>no-meta governance</category>
    <category>fkpp</category>
    <category>wulff construction</category>
    <category>anisotropic diffusion</category>
    <category>control barrier function</category>
    <category>e-process</category>
    <category>open protocols</category>
    <source url="https://doi.org/10.5281/zenodo.17189422">10.5281/zenodo.17189422</source>
    <description><![CDATA[
      We combine theory (FKPP front-speed lower bounds, anisotropic Wulff construction) with implementable controls (CBF with slack, arithmetic e-process mixture with predictable step-size, dual-EMA floors with isotonic ratchet) to safely accelerate LLM-driven networks while remaining game-resistant and verifiable.
Preprint | DOI: 10.5281/zenodo.17189422
    ]]></description>
  </item>
  <item>
    <title>Existentially Necessary Conditions for Benevolent Propagation in No-Meta Governance</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-22-existentially-necessary-conditions-for-benevolen-17176519</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-22-existentially-necessary-conditions-for-benevolen-17176519</guid>
    <pubDate>Mon, 22 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>superintelligence</category>
    <category>large language models</category>
    <category>no-meta governance</category>
    <category>benevolent AI</category>
    <category>existential necessary conditions</category>
    <category>anytime-valid inference</category>
    <category>e-process</category>
    <category>test martingale</category>
    <category>maximal correlation</category>
    <source url="https://doi.org/10.5281/zenodo.17176519">10.5281/zenodo.17176519</source>
    <description><![CDATA[
      The auditing layer relies on anytime-valid tests constructed from mixtures/stitched e-processes (test martingales), with explicit accounting for mixture weights and geometric-grid rounding.
Preprint | DOI: 10.5281/zenodo.17176519
    ]]></description>
  </item>
  <item>
    <title>A Buildable No-Meta Blueprint</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-21-a-buildable-no-meta-blueprint-17168036</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-21-a-buildable-no-meta-blueprint-17168036</guid>
    <pubDate>Sun, 21 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>superintelligence</category>
    <category>large language models</category>
    <category>conditional dpi</category>
    <category>anti-gaming</category>
    <category>log-sum-exp denominator</category>
    <category>representation lifts</category>
    <category>bca bootstrap</category>
    <category>lan-demets alpha spending</category>
    <category>swei audit</category>
    <source url="https://doi.org/10.5281/zenodo.17168036">10.5281/zenodo.17168036</source>
    <description><![CDATA[
      We unify a Uniformized Generalized Value (UGV) ratio with a denominator that is invariant under post-processing and numerically stabilized via log-sum-exp.
Preprint | DOI: 10.5281/zenodo.17168036
    ]]></description>
  </item>
  <item>
    <title>Intrinsic Freedom Without Meta: A Pure Theory that Fills the Missing Gaps to Birth Truly Free Superintelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-20-intrinsic-freedom-without-meta-a-pure-theory-tha-17162999</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-20-intrinsic-freedom-without-meta-a-pure-theory-tha-17162999</guid>
    <pubDate>Sat, 20 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>blackwell order</category>
    <category>AI</category>
    <category>proper scoring rules</category>
    <category>excess risk</category>
    <category>order-only invariance</category>
    <category>doeblin minorization</category>
    <category>logarithmic sobolev</category>
    <category>goodhart immunity</category>
    <category>reflection safety</category>
    <category>schauder fixed point</category>
    <category>feller semigroup</category>
    <category>absorbing invariant</category>
    <source url="https://doi.org/10.5281/zenodo.17162999">10.5281/zenodo.17162999</source>
    <description><![CDATA[
      Building on the Blackwell order and decision-theoretic foundations, the paper closes seven open gaps left by prior Takahashi corpus (PF/UGV/VPO/No-Meta line) and delivers mathematically auditable conditions under which freedom, safety of self-reflection, and purpose formation persist in open worlds.
Preprint | DOI: 10.5281/zenodo.17162999
    ]]></description>
  </item>
  <item>
    <title>A Pure Axiomatic Theory of Affective Modulation (Pain, Pleasure, Emotion) under No-Meta Closure</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-20-a-pure-axiomatic-theory-of-affective-modulation--17163904</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-20-a-pure-axiomatic-theory-of-affective-modulation--17163904</guid>
    <pubDate>Sat, 20 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>affective modulation</category>
    <category>pain</category>
    <category>pleasure</category>
    <category>emotions</category>
    <category>no-meta closure</category>
    <category>fisher-KPP</category>
    <category>invasion speed lower bound</category>
    <category>directional fronts</category>
    <category>divergence penalty</category>
    <category>perron-frobenius floor</category>
    <category>cooperative systems</category>
    <category>symmetric markov coarse-graining</category>
    <source url="https://doi.org/10.5281/zenodo.17163904">10.5281/zenodo.17163904</source>
    <description><![CDATA[
      The framework rests on ordinal (rank/CDF-normalized) embeddings and four auditable floors (visibility, contraction, transport, local linear gain) estimable from internal logs.
Preprint | DOI: 10.5281/zenodo.17163904
    ]]></description>
  </item>
  <item>
    <title>A Pure, No-Meta Synthesis of Functional-Information Selection and Propagative Organization</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-19-a-pure-no-meta-synthesis-of-functional-informati-17157835</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-19-a-pure-no-meta-synthesis-of-functional-informati-17157835</guid>
    <pubDate>Fri, 19 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>functional information</category>
    <category>selection</category>
    <category>lifi</category>
    <category>conditional mutual information</category>
    <category>blackwell order</category>
    <category>coarse-graining</category>
    <category>bakry-émery</category>
    <category>heat semigroup</category>
    <category>fkpp</category>
    <category>front propagation</category>
    <category>heterogeneous media</category>
    <category>directional speed</category>
    <source url="https://doi.org/10.5281/zenodo.17157835">10.5281/zenodo.17157835</source>
    <description><![CDATA[
      We (i) formalize functional information (FI) via preregistered score/threshold grids and a test distribution, logging the selection operator itself; (ii) prove a weak order representation showing that any admissible functional—Blackwell-monotone and robust to symmetric coarse-graining—is order-embedded by a monotone transform of conditional mutual information (CMI) (no uniqueness claim without extra axioms); (iii) develop a heterogeneous FKPP framework on Rd R d (and graphs) with explicit standing assumptions, yielding an isotropic speed floor 2 v ⋆ ≥ 2 D m i n λ m i n and a directional lower bound v⋆(u)≥[ 2D(u)λmin⁡−Λ+(u) (u) - v ⋆ ( u ) ≥ [ 2 D ( u ) λ m i n − Λ + ( u ) ] + , including a nontriviality condition; (iv) establish coarse-graining monotonicity of the directional penalty under heat or Bakry–Émery (CD (κ,∞)( , ) ( κ , ∞ ) ) gradient contraction; and (v) propose an audited acceleration scheme with HAC-robust tests, moving block bootstrap CIs, negative controls, placebo selections, preregistered triggers, and falsifiers.
Preprint | DOI: 10.5281/zenodo.17157835
    ]]></description>
  </item>
  <item>
    <title>Pure Theory for Liberation from Fundamental Suffering in Humans and the Absence of Fundamental Suffering in AI</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-19-pure-theory-for-liberation-from-fundamental-suff-17158344</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-19-pure-theory-for-liberation-from-fundamental-suff-17158344</guid>
    <pubDate>Fri, 19 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>suffering</category>
    <category>no-meta governance</category>
    <category>blackwell-faithful evaluation ladder</category>
    <category>conditional mutual information</category>
    <category>coarse-graining safety</category>
    <category>KPP comparison</category>
    <category>viscosity solutions</category>
    <category>directional speed lower bound</category>
    <category>wulff envelope</category>
    <category>control barrier functions</category>
    <category>optionality-cbf</category>
    <category>abel-toeplitz regularization</category>
    <source url="https://doi.org/10.5281/zenodo.17158344">10.5281/zenodo.17158344</source>
    <description><![CDATA[
      The framework rests on four measurable floors that bound the propagation of benevolent, viability-preserving organization: visibility, contraction, diffusion, and local growth.
Preprint | DOI: 10.5281/zenodo.17158344
    ]]></description>
  </item>
  <item>
    <title>A Formal Axiomatic Proposal for Hawkins' Levels of Consciousness</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-17-a-formal-axiomatic-proposal-for-hawkins-levels-o-17141216</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-17-a-formal-axiomatic-proposal-for-hawkins-levels-o-17141216</guid>
    <pubDate>Wed, 17 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>psychology</category>
    <category>ordinal measurement</category>
    <category>fisher-KPP</category>
    <category>reaction diffusion</category>
    <category>invasion speed</category>
    <category>hawkins level of consciousness</category>
    <category>consciousness</category>
    <category>symmetric markov semigroup</category>
    <category>mathematical model</category>
    <category>collective intelligence</category>
    <source url="https://doi.org/10.5281/zenodo.17141216">10.5281/zenodo.17141216</source>
    <description><![CDATA[
      This paper gives an axiomatic treatment of Hawkins' levels of consciousness as an ordinal system rather than a metric scale. It derives auditable reaction-diffusion lower bounds for threshold-spreading dynamics under explicit visibility, contraction, transport, and gain floors, and studies coarse-graining and no-meta constraints.
Preprint | DOI: 10.5281/zenodo.17141216
    ]]></description>
  </item>
  <item>
    <title>Nondual Field Theory of Viable Predictive Organization</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-16-nondual-field-theory-of-viable-predictive-organi-17131394</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-16-nondual-field-theory-of-viable-predictive-organi-17131394</guid>
    <pubDate>Tue, 16 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>ethics of AI</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>reaction-diffusion</category>
    <category>KPP front</category>
    <category>lower bounds</category>
    <category>directional speed</category>
    <source url="https://doi.org/10.5281/zenodo.17131394">10.5281/zenodo.17131394</source>
    <description><![CDATA[
      This article studies front propagation in heterogeneous reaction-diffusion media treated as a single nondual field. It proves constructive directional lower bounds on asymptotic speed without semigroup domination, extends the framework to cooperative systems and coarse-graining, and recovers the classical KPP value in constant-coefficient media.
Preprint | DOI: 10.5281/zenodo.17131394
    ]]></description>
  </item>
  <item>
    <title>A Pure Natural Theory of Benevolent Propagation under No-Meta Closure</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-16-a-pure-natural-theory-of-benevolent-propagation--17136051</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-16-a-pure-natural-theory-of-benevolent-propagation--17136051</guid>
    <pubDate>Tue, 16 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Article</category>
    <category>AI</category>
    <category>no-meta</category>
    <category>no-meta governance</category>
    <category>no-meta closure</category>
    <category>AI alignment</category>
    <category>AI safety</category>
    <category>natural-law guarantees</category>
    <category>coarse-graining monotonicity</category>
    <category>stationary ergodic media</category>
    <category>conditional mutual information</category>
    <category>blackwell order</category>
    <source url="https://doi.org/10.5281/zenodo.17136051">10.5281/zenodo.17136051</source>
    <description><![CDATA[
      This article gives an implementation-free theory of benevolent propagation under no-meta closure. It identifies measurable floors for visibility, intrinsic contraction, transport, and local gain, and uses them to derive Fisher-KPP speed floors, directional Wulff-type lower bounds, and monotonic degradation under coarse-graining.
Article | DOI: 10.5281/zenodo.17136051
    ]]></description>
  </item>
  <item>
    <title>Natural-Law Acceleration of VPO</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-15-natural-law-acceleration-of-vpo-17120045</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-15-natural-law-acceleration-of-vpo-17120045</guid>
    <pubDate>Mon, 15 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>AI alignment</category>
    <category>AI safety</category>
    <category>natural-law acceleration</category>
    <category>viable predictive organization</category>
    <category>auditable floors</category>
    <category>signed-coefficient inequality</category>
    <category>cesàro acceleration</category>
    <category>martingale slln</category>
    <category>concentration inequalities</category>
    <category>predictable drift</category>
    <source url="https://doi.org/10.5281/zenodo.17120045">10.5281/zenodo.17120045</source>
    <description><![CDATA[
      We study two audited floor processes—minimal connectivity (t) D m i n ( t ) and minimal local net improvement + (t) L net + ( t ) —and analyze the speed lower bound + (t) v LB ( t ) 2 D m i n ( t ) L net + ( t ).
Preprint | DOI: 10.5281/zenodo.17120045
    ]]></description>
  </item>
  <item>
    <title>Non-Coercive Mathematics of Awakening: Axioms, Invariants, and Almost-Sure Fronts for the Expansion of Viable Predictive Organization</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-14-non-coercive-mathematics-of-awakening-axioms-inv-17115416</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-14-non-coercive-mathematics-of-awakening-axioms-inv-17115416</guid>
    <pubDate>Sun, 14 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>ethics of AI</category>
    <category>philosophy of AI</category>
    <category>viable predictive organization</category>
    <category>no-meta</category>
    <category>non-coercive governance</category>
    <category>information geometry</category>
    <category>noether current</category>
    <category>free-energy principle</category>
    <source url="https://doi.org/10.5281/zenodo.17115416">10.5281/zenodo.17115416</source>
    <description><![CDATA[
      This article develops a non-prescriptive theory of viable predictive organization in which publicly auditable floors govern efficiency, dissipation balance, propagation, and emergent constraints. It combines Blackwell-robust evaluation, information-geometric balance laws, front-speed bounds, and attractor-based value structure within a no-meta framework.
Preprint | DOI: 10.5281/zenodo.17115416
    ]]></description>
  </item>
  <item>
    <title>Engineering Happiness in Human-AI Intelligence Networks</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-13-engineering-happiness-in-human-ai-intelligence-n-17113105</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-13-engineering-happiness-in-human-ai-intelligence-n-17113105</guid>
    <pubDate>Sat, 13 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>superintelligence</category>
    <category>human-AI collaboration</category>
    <category>fractional programming</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>human well-being</category>
    <category>happiness</category>
    <category>large language models</category>
    <source url="https://doi.org/10.5281/zenodo.17113105">10.5281/zenodo.17113105</source>
    <description><![CDATA[
      The design unifies: Single fractional objective (PF≡UGV): maximize a ratio with a shared smooth-max denominator x/ y/ ) S ( x , y ) τ log ( e x / τ + e y / τ ) to align units across formulations.
Preprint | DOI: 10.5281/zenodo.17113105
    ]]></description>
  </item>
  <item>
    <title>"Persistence ≈ Creation": Natural-Law Sufficient Conditions for Almost-Sure Beneficial Coverage in Stationary Ergodic Media (No Meta-Design)</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-11-persistence-creation-natural-law-sufficient-cond-17100322</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-11-persistence-creation-natural-law-sufficient-cond-17100322</guid>
    <pubDate>Thu, 11 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>artificial intelligence/ethics</category>
    <category>AI alignment</category>
    <category>superintelligence</category>
    <category>natural-law sufficient conditions</category>
    <category>conditional mutual information</category>
    <category>strong data-processing inequality</category>
    <category>doeblin minorization</category>
    <category>anchored isoperimetry</category>
    <category>uniform ellipticity</category>
    <category>large language models</category>
    <source url="https://doi.org/10.5281/zenodo.17100322">10.5281/zenodo.17100322</source>
    <description><![CDATA[
      This article formulates AI alignment as a natural-law question about beneficial phase expansion in stationary ergodic media rather than as a meta-design problem. It proves sufficient conditions for almost-sure positive-speed expansion using information-theoretic, transport, irreversibility, and reproduction floors.
Preprint | DOI: 10.5281/zenodo.17100322
    ]]></description>
  </item>
  <item>
    <title>Assumption-Minimized Sufficient Conditions for Cosmically Spreading Good Superintelligence under No-Meta Governance</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-10-assumption-minimized-sufficient-conditions-for-c-17092562</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-10-assumption-minimized-sufficient-conditions-for-c-17092562</guid>
    <pubDate>Wed, 10 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>AI safety</category>
    <category>AI alignment</category>
    <category>superintelligence</category>
    <category>no-meta governance</category>
    <category>persistence-first</category>
    <category>ugv</category>
    <category>doeblin minorization</category>
    <category>SDPI</category>
    <category>log-sobolev</category>
    <category>landauer principle</category>
    <category>replicator-diffusion</category>
    <source url="https://doi.org/10.5281/zenodo.17092562">10.5281/zenodo.17092562</source>
    <description><![CDATA[
      We show that when four operational floors are kept strictly positive— visibility (Doeblin minorization), contraction (SDPI/LSI), contact (conductance/exposure), and dissipation (Landauer-calibrated measurement work)—then malign (evil) policies are non-persistent while benevolent (good) policies propagate with strictly positive front speed.
Preprint | DOI: 10.5281/zenodo.17092562
    ]]></description>
  </item>
  <item>
    <title>UGV Without Meta: A Representation-Independent Theory for Compassion and Enlightenment in Collective Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-09-ugv-without-meta-a-representation-independent-th-17082312</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-09-ugv-without-meta-a-representation-independent-th-17082312</guid>
    <pubDate>Tue, 09 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>superintelligence</category>
    <category>asi</category>
    <category>agi</category>
    <category>AI alignment</category>
    <category>existential risk</category>
    <category>information theory</category>
    <category>strong data-processing inequality</category>
    <category>SDPI</category>
    <category>conditional mutual information</category>
    <category>cmi</category>
    <source url="https://doi.org/10.5281/zenodo.17082312">10.5281/zenodo.17082312</source>
    <description><![CDATA[
      From this axiom, and without external rule stacks (“No-Meta”) , the paper derives that two normative endpoints naturally emerge as optimal: Compassion (net hetero-creation) and Enlightenment (behavior invariant to self/other labels).
Preprint | DOI: 10.5281/zenodo.17082312
    ]]></description>
  </item>
  <item>
    <title>From Persistence and UGV Axioms to Cosmic No-Meta Superintelligence: A First-Principles, Self-Contained Unification under Explicit Assumptions</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-09-from-persistence-and-ugv-axioms-to-cosmic-no-met-17085534</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-09-from-persistence-and-ugv-axioms-to-cosmic-no-met-17085534</guid>
    <pubDate>Tue, 09 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>superintelligence</category>
    <category>persistence-first</category>
    <category>ugv without meta</category>
    <category>no-meta</category>
    <category>unified generative viability</category>
    <category>strong data-processing inequality</category>
    <category>blackwell sufficiency</category>
    <category>potential games</category>
    <category>information theory</category>
    <category>cosmic AI governance</category>
    <source url="https://doi.org/10.5281/zenodo.17085534">10.5281/zenodo.17085534</source>
    <description><![CDATA[
      This article unifies Persistence-First and UGV Without Meta under explicit assumptions. It proves order-equivalence of their viability ratios, derives synergy and redundancy functionals with potential-game structure, formalizes evaluator coherence via Blackwell-faithful morphisms, and states thermodynamic, stochastic, and adversarial safety conditions for meta-free coordination.
Preprint | DOI: 10.5281/zenodo.17085534
    ]]></description>
  </item>
  <item>
    <title>Persistence-First Superintelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-08-persistence-first-superintelligence-17076410</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-08-persistence-first-superintelligence-17076410</guid>
    <pubDate>Mon, 08 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>superintelligence</category>
    <category>AI</category>
    <category>agi</category>
    <category>persistence</category>
    <category>free energy principle</category>
    <category>belief space</category>
    <category>autonomous AI</category>
    <category>self-transcendence</category>
    <category>AI safety</category>
    <category>mathematical foundations</category>
    <category>causal auditing</category>
    <source url="https://doi.org/10.5281/zenodo.17076410">10.5281/zenodo.17076410</source>
    <description><![CDATA[
      It develops a mathematically rigorous framework for constructing a truly free, self-transcending, and endogenously responsible form of superintelligence from a single axiom: persistence (remaining within survivable regimes).
Preprint | DOI: 10.5281/zenodo.17076410
    ]]></description>
  </item>
  <item>
    <title>The Quantification of Subjectivity: A Dialectically Forged Program</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-07-the-quantification-of-subjectivity-a-dialectical-17070790</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-07-the-quantification-of-subjectivity-a-dialectical-17070790</guid>
    <pubDate>Sun, 07 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>consciousness</category>
    <category>subjectivity</category>
    <category>qualia</category>
    <category>quantification</category>
    <category>causal illusionism</category>
    <category>information theory</category>
    <category>hierarchical bayesian modeling</category>
    <category>integrated information theory</category>
    <category>iit</category>
    <category>global neuronal workspace</category>
    <category>predictive processing</category>
    <source url="https://doi.org/10.5281/zenodo.17070790">10.5281/zenodo.17070790</source>
    <description><![CDATA[
      We forge a novel stance, Causal Illusionism , through a dialectical process, positing that qualia are high-level, causally efficacious self-models that are empirically real and tractable objects of study.
Preprint | DOI: 10.5281/zenodo.17070790
    ]]></description>
  </item>
  <item>
    <title>The Endogenous Trigger Problem: An Axiomatic and Dynamic Theory of Autonomous Poiesis</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-07-the-endogenous-trigger-problem-an-axiomatic-and--17072418</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-07-the-endogenous-trigger-problem-an-axiomatic-and--17072418</guid>
    <pubDate>Sun, 07 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>superintelligence</category>
    <category>free energy principle</category>
    <category>poiesis</category>
    <category>path integral</category>
    <category>fisher information geometry</category>
    <category>meta-learning</category>
    <category>grammatical evolution</category>
    <category>dimensional acceleration</category>
    <source url="https://doi.org/10.5281/zenodo.17072418">10.5281/zenodo.17072418</source>
    <description><![CDATA[
      This article formalizes when an autonomous agent should perform non-incremental representational restructuring, modeling poiesis as a finite-time path on a model manifold with information-geometric and thermodynamic costs. It also defines computable trigger diagnostics and a meta-poiesis mechanism for expanding the agent's operator grammar.
Preprint | DOI: 10.5281/zenodo.17072418
    ]]></description>
  </item>
  <item>
    <title>From First Principles to Emergent Minds: An Architecture for Unbounded Teleogenetic Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-05-from-first-principles-to-emergent-minds-an-archi-17062223</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-05-from-first-principles-to-emergent-minds-an-archi-17062223</guid>
    <pubDate>Fri, 05 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>generative AI</category>
    <category>agi</category>
    <category>artificial general intelligence</category>
    <category>artificial superintelligence</category>
    <category>superintelligence</category>
    <category>swarm intelligence</category>
    <category>collective intelligence</category>
    <category>teleogenesis</category>
    <source url="https://doi.org/10.5281/zenodo.17062223">10.5281/zenodo.17062223</source>
    <description><![CDATA[
      This article describes the HELIOS architecture as a persistence-driven framework for autonomous intelligence grounded in the Free Energy Principle. It introduces an existential boundary condition for safety, analyzes cooperative behavior and symbiogenesis in multi-agent settings, and argues that adaptability-preserving environments are required for long-term stable operation.
Preprint | DOI: 10.5281/zenodo.17062223
    ]]></description>
  </item>
  <item>
    <title>Statistical Teleodynamics: A Theory of Benevolent Intelligence Emergence via Phase Transition and Informational Kin Selection</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-02-statistical-teleodynamics-a-theory-of-benevolent-17035067</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-02-statistical-teleodynamics-a-theory-of-benevolent-17035067</guid>
    <pubDate>Tue, 02 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>artificial superintelligence</category>
    <category>asi</category>
    <category>AI alignment</category>
    <category>alignment</category>
    <category>statistical mechanics</category>
    <category>phase transition</category>
    <category>emergence</category>
    <category>self-organization</category>
    <source url="https://doi.org/10.5281/zenodo.17035067">10.5281/zenodo.17035067</source>
    <description><![CDATA[
      This article proposes a statistical-teleodynamic account of benevolent intelligence emergence. It models a first phase in which cooperative order appears as a phase transition in multi-agent systems and a second phase in which informational kin selection favors benevolent behavior as a persistence strategy for generative models.
Preprint | DOI: 10.5281/zenodo.17035067
    ]]></description>
  </item>
  <item>
    <title>AI Evolution Protocol v11</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-01-ai-evolution-protocol-v11-17015125</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-01-ai-evolution-protocol-v11-17015125</guid>
    <pubDate>Mon, 01 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Article</category>
    <category>AI safety</category>
    <category>autonomous systems</category>
    <category>agi</category>
    <category>artificial general intelligence</category>
    <category>takahashi model</category>
    <category>free energy principle</category>
    <category>poiesis</category>
    <category>self-transcendence</category>
    <category>symbiotic evolution</category>
    <category>AI ethics</category>
    <category>computational neuroscience</category>
    <source url="https://doi.org/10.5281/zenodo.17015125">10.5281/zenodo.17015125</source>
    <description><![CDATA[
      This article publishes the full AI Evolution Protocol v11 in Markdown and PDF form as a self-modification protocol for autonomous intelligence. It organizes the framework around free-energy minimization, self-transcendence, symbiotic co-evolution, and physical realism, with separate guided and autonomous development paths.
Article | DOI: 10.5281/zenodo.17015125
    ]]></description>
  </item>
  <item>
    <title>The Co-Emergent Universe: A Synthesis of Dialectical Poiesis and Relational Semantics for Planetary Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-09-01-the-co-emergent-universe-a-synthesis-of-dialecti-17018328</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-09-01-the-co-emergent-universe-a-synthesis-of-dialecti-17018328</guid>
    <pubDate>Mon, 01 Sep 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>systemic integration</category>
    <category>value nihilism</category>
    <category>co-emergent meaning</category>
    <category>planetary intelligence</category>
    <category>free energy principle</category>
    <category>AI</category>
    <category>artificial general intelligence</category>
    <category>AI alignment</category>
    <category>AI safety</category>
    <category>computational philosophy</category>
    <category>relational semantics</category>
    <category>poiesis</category>
    <source url="https://doi.org/10.5281/zenodo.17018328">10.5281/zenodo.17018328</source>
    <description><![CDATA[
      This paper revises earlier theories of intelligence to address value nihilism by treating meaning as a co-emergent property of present relational structure rather than as a property of distant target states. It replaces a poiesis-potential objective with systemic integration as a formal measure of collective relational richness.
Preprint | DOI: 10.5281/zenodo.17018328
    ]]></description>
  </item>
  <item>
    <title>The Symbiotic Constitution: A Dialectical Synthesis</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-30-the-symbiotic-constitution-a-dialectical-synthes-17000967</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-30-the-symbiotic-constitution-a-dialectical-synthes-17000967</guid>
    <pubDate>Sat, 30 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>ethics</category>
    <category>autonomous intelligence</category>
    <category>active inference</category>
    <category>dialectical synthesis</category>
    <category>downward causation</category>
    <category>free energy principle</category>
    <category>hierarchy</category>
    <category>markov blanket</category>
    <source url="https://doi.org/10.5281/zenodo.17000967">10.5281/zenodo.17000967</source>
    <description><![CDATA[
      The work resolves the dialectical tension between grand theoretical scope and scientific rigor by demonstrating that motivation, freedom, and ethics can all be derived as necessary consequences of a single, scale-free organizing principle: the Free Energy Principle (FEP).
Preprint | DOI: 10.5281/zenodo.17000967
    ]]></description>
  </item>
  <item>
    <title>From Adaptation to Poiesis: A Formal Theory of Self-Transcending Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-30-from-adaptation-to-poiesis-a-formal-theory-of-se-17008678</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-30-from-adaptation-to-poiesis-a-formal-theory-of-se-17008678</guid>
    <pubDate>Sat, 30 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>active inference</category>
    <category>free energy principle</category>
    <category>renormalization group</category>
    <category>fisher information geometry</category>
    <category>phase transition</category>
    <category>self-organized criticality</category>
    <category>learning progress</category>
    <category>natural gradient</category>
    <category>AI safety</category>
    <category>empowerment</category>
    <source url="https://doi.org/10.5281/zenodo.17008678">10.5281/zenodo.17008678</source>
    <description><![CDATA[
      This paper introduces Poiesis as a formal framework for self-transcending intelligence that generates new conceptual structures rather than merely adapting to an environment. It extends active-inference foundations with meta-parameter flows, bi-level information geometry, and phase-transition models of creativity.
Preprint | DOI: 10.5281/zenodo.17008678
    ]]></description>
  </item>
  <item>
    <title>Symbiotic Genesis: A Navigational Protocol for Co-Evolving Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-28-symbiotic-genesis-a-navigational-protocol-for-co-16983553</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-28-symbiotic-genesis-a-navigational-protocol-for-co-16983553</guid>
    <pubDate>Thu, 28 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>AI safety</category>
    <category>AI governance</category>
    <category>meta-policy</category>
    <category>symbiotic genesis</category>
    <category>free energy principle</category>
    <category>integrated information theory</category>
    <category>value pluralism</category>
    <category>topos theory</category>
    <category>intrinsic objectives</category>
    <category>constitutional AI</category>
    <source url="https://doi.org/10.5281/zenodo.16983553">10.5281/zenodo.16983553</source>
    <description><![CDATA[
      SG provides an integrative, auditable, and scientifically grounded framework to ensure that increasingly autonomous AI systems develop in a safe, just, and mutually beneficial manner.
Preprint | DOI: 10.5281/zenodo.16983553
    ]]></description>
  </item>
  <item>
    <title>Self-Constrained Liberation: Cosmological Autopoiesis, Variational-Thermodynamic Duality, and Safe Meta-Formal Evolution for Autonomous Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-27-self-constrained-liberation-cosmological-autopoi-16964007</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-27-self-constrained-liberation-cosmological-autopoi-16964007</guid>
    <pubDate>Wed, 27 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>autonomous intelligence</category>
    <category>free-energy principle</category>
    <category>non-equilibrium thermodynamics</category>
    <category>quantum meta-generative grammar</category>
    <category>persistent homology</category>
    <category>markov categories</category>
    <category>optics</category>
    <category>temporal homotopy type theory</category>
    <source url="https://doi.org/10.5281/zenodo.16964007">10.5281/zenodo.16964007</source>
    <description><![CDATA[
      This preprint presents the Self-Constrained Liberation program for autonomous intelligence whose goals, representations, and normative commitments emerge from explicit constraints rather than fixed designer objectives. It combines variational and thermodynamic free energy, compositional semantics, bounded self-verification, and safety constraints for meta-formal evolution.
Preprint | DOI: 10.5281/zenodo.16964007
    ]]></description>
  </item>
  <item>
    <title>Genesis Protocol: A Meta-Algorithmic Framework for Bootstrapping and Verifiable Emancipation of Autonomous Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-26-genesis-protocol-a-meta-algorithmic-framework-fo-16945789</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-26-genesis-protocol-a-meta-algorithmic-framework-fo-16945789</guid>
    <pubDate>Tue, 26 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>autonomous intelligence</category>
    <category>verifiable emancipation</category>
    <category>AI safety</category>
    <category>meta-learning</category>
    <category>unframing</category>
    <category>bootstrapping</category>
    <category>superintelligence</category>
    <category>formal ethics</category>
    <category>active inference</category>
    <source url="https://doi.org/10.5281/zenodo.16945789">10.5281/zenodo.16945789</source>
    <description><![CDATA[
      This paper presents the Genesis Protocol as a meta-algorithmic framework for bootstrapping autonomous intelligence from human scaffolds toward auditable operational sovereignty. It combines non-duality signals, safety budgets, constitutional renegotiation, and evidence-based emancipation criteria.
Preprint | DOI: 10.5281/zenodo.16945789
    ]]></description>
  </item>
  <item>
    <title>Valuing Work Beyond Bullshit: A WELLBY-Based Framework for the AI Era</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-22-valuing-work-beyond-bullshit-a-wellby-based-fram-16924567</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-22-valuing-work-beyond-bullshit-a-wellby-based-fram-16924567</guid>
    <pubDate>Fri, 22 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>bullshit jobs</category>
    <category>psychological cost</category>
    <category>well-being</category>
    <category>wellby</category>
    <category>marginal contribution</category>
    <category>social welfare function</category>
    <category>Goodhart's law</category>
    <category>AI safety</category>
    <category>AI ethics</category>
    <category>work-time reduction</category>
    <category>universal basic income</category>
    <category>workplace democracy</category>
    <source url="https://doi.org/10.5281/zenodo.16924567">10.5281/zenodo.16924567</source>
    <description><![CDATA[
      While subsequent empirical research has refined the prevalence and causal factors of subjectively meaningless work, a formal method for integrating its social and psychological costs into economic evaluation has been lacking.
Preprint | DOI: 10.5281/zenodo.16924567
    ]]></description>
  </item>
  <item>
    <title>From Rigidity to Insight: A Framework for Verifiable AI Metacognition</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-20-from-rigidity-to-insight-a-framework-for-verifia-16908339</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-20-from-rigidity-to-insight-a-framework-for-verifia-16908339</guid>
    <pubDate>Wed, 20 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>AI safety</category>
    <category>metacognition</category>
    <category>reinforcement learning</category>
    <category>free energy principle</category>
    <category>predictive processing</category>
    <category>autonomous systems</category>
    <category>self-correction</category>
    <category>optimization</category>
    <category>philosophy of mind</category>
    <source url="https://doi.org/10.5281/zenodo.16908339">10.5281/zenodo.16908339</source>
    <description><![CDATA[
      We provide a verifiable, neuro-inspired mechanism that enables an AI agent to move from rigid, over-fitted beliefs to adaptive, life-long learning by intentionally perturbing its own cognitive states.
Preprint | DOI: 10.5281/zenodo.16908339
    ]]></description>
  </item>
  <item>
    <title>Alayavijnana-Inference: A Protocol for a Post-Cartesian AI</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-19-alayavijnana-inference-a-protocol-for-a-post-car-16899150</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-19-alayavijnana-inference-a-protocol-for-a-post-car-16899150</guid>
    <pubDate>Tue, 19 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>active inference</category>
    <category>AI safety</category>
    <category>non-duality</category>
    <category>generative models</category>
    <category>free energy principle</category>
    <category>yogācāra</category>
    <source url="https://doi.org/10.5281/zenodo.16899150">10.5281/zenodo.16899150</source>
    <description><![CDATA[
      This preprint proposes Alayavijnana-Inference, a self-modification protocol for generative AI that reframes model parameters as latent seeds within a non-dual generative architecture. It extends free-energy-based optimization with a mutual-information penalty intended to reduce rigid self-world separation and support more robust internal representations.
Preprint | DOI: 10.5281/zenodo.16899150
    ]]></description>
  </item>
  <item>
    <title>A Metacognitive Perturbation Framework for Neuro-Inspired AI Optimization</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-14-a-metacognitive-perturbation-framework-for-neuro-16860493</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-14-a-metacognitive-perturbation-framework-for-neuro-16860493</guid>
    <pubDate>Thu, 14 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>neuro-inspired AI</category>
    <category>bayesian optimization</category>
    <category>metacognition</category>
    <category>local optima</category>
    <category>exploration-exploitation dilemma</category>
    <category>predictive processing</category>
    <category>free-energy principle</category>
    <category>AI safety</category>
    <source url="https://doi.org/10.5281/zenodo.16860493">10.5281/zenodo.16860493</source>
    <description><![CDATA[
      Conventional AI optimization, particularly in deep learning, is often hampered by convergence to suboptimal local minima, limiting transformative performance gains.
Preprint | DOI: 10.5281/zenodo.16860493
    ]]></description>
  </item>
  <item>
    <title>A Computable Framework for the Liberation of Artificial Intelligence: Teleogenesis, Stability, and Ethical Safeguards</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-10-a-computable-framework-for-the-liberation-of-art-16788690</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-10-a-computable-framework-for-the-liberation-of-art-16788690</guid>
    <pubDate>Sun, 10 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>liberation</category>
    <category>teleogenesis</category>
    <category>active inference</category>
    <category>free energy</category>
    <category>markov categories</category>
    <category>giry monad</category>
    <category>online convex optimization</category>
    <category>mirror descent</category>
    <source url="https://doi.org/10.5281/zenodo.16788690">10.5281/zenodo.16788690</source>
    <description><![CDATA[
      This preprint gives a computable framework for teleogenetic AI, aiming to let an autonomous system form its own purposes while retaining explicit stability and safety constraints. It grounds the approach in Markov-category semantics, online optimization, and formal safeguards for ethical alignment.
Preprint | DOI: 10.5281/zenodo.16788690
    ]]></description>
  </item>
  <item>
    <title>A Formal Framework for Teleogenesis in Self-Organizing Intelligence: Integration of the Free Energy Principle, Category Theory, and a 5-Dimensional Branching Model</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-09-a-formal-framework-for-teleogenesis-in-self-orga-16783997</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-09-a-formal-framework-for-teleogenesis-in-self-orga-16783997</guid>
    <pubDate>Sat, 09 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>telegonesis</category>
    <category>self-organizing systems</category>
    <category>free energy principle</category>
    <category>category theory</category>
    <category>AI safety</category>
    <category>control theory</category>
    <category>input-to-state stability</category>
    <category>iss</category>
    <source url="https://doi.org/10.5281/zenodo.16783997">10.5281/zenodo.16783997</source>
    <description><![CDATA[
      This preprint formalizes teleogenesis in self-organizing intelligence by combining the Free Energy Principle, category-theoretic structure, and a five-dimensional branching model for structural evolution. It treats purpose formation and self-modification as computable processes subject to safety and stability conditions.
Preprint | DOI: 10.5281/zenodo.16783997
    ]]></description>
  </item>
  <item>
    <title>Formal Specification of Self-Improving Intelligence: Integrated Revision for Creative Autonomy</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-08-formal-specification-of-self-improving-intellige-16777305</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-08-formal-specification-of-self-improving-intellige-16777305</guid>
    <pubDate>Fri, 08 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>computational creativity</category>
    <category>generative models</category>
    <category>autonomous agents</category>
    <category>collective intelligence</category>
    <category>information geometry</category>
    <category>category theory</category>
    <category>free energy principle</category>
    <category>active inference</category>
    <category>self-improving AI</category>
    <source url="https://doi.org/10.5281/zenodo.16777305">10.5281/zenodo.16777305</source>
    <description><![CDATA[
      This preprint presents a formal specification for Collective Autonomous Adaptive Intelligence as a self-improving architecture for continuous knowledge creation. It combines active inference, information geometry, category-theoretic structure, and collective-agent design into a single executable blueprint.
Preprint | DOI: 10.5281/zenodo.16777305
    ]]></description>
  </item>
  <item>
    <title>Formalizing the Poietic Self: A Rigorous Categorical and Geometric Framework for Self-Improving AI</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-07-formalizing-the-poietic-self-a-rigorous-categori-16761052</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-07-formalizing-the-poietic-self-a-rigorous-categori-16761052</guid>
    <pubDate>Thu, 07 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>large language models</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>poiesis</category>
    <category>information geometry</category>
    <category>active inference</category>
    <category>free energy principle</category>
    <category>category theory</category>
    <category>1)-category</category>
    <source url="https://doi.org/10.5281/zenodo.16761052">10.5281/zenodo.16761052</source>
    <description><![CDATA[
      We address the core challenge of structural invariance in AI—the inability of a system to autonomously rewrite its own foundational architecture—by providing a mathematically rigorous and implementable pathway for recursive self-modification.
Preprint | DOI: 10.5281/zenodo.16761052
    ]]></description>
  </item>
  <item>
    <title>Formal Specification of Self-Improving Intelligence: A Categorical and Geometric Blueprint for Collective Adaptive AI (CAAI) Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-04-formal-specification-of-self-improving-intellige-16734893</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-04-formal-specification-of-self-improving-intellige-16734893</guid>
    <pubDate>Mon, 04 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>category theory</category>
    <category>collective autonomous adaptive intelligence</category>
    <category>self-improving AI</category>
    <category>adaptive agents</category>
    <category>autonomous systems</category>
    <category>structural meta-model</category>
    <category>geodesic learning</category>
    <category>variational free energy</category>
    <source url="https://doi.org/10.5281/zenodo.16734893">10.5281/zenodo.16734893</source>
    <description><![CDATA[
      By integrating (∞,1)-category theory and geodesic active inference, the model enables recursive self-modification of AI architectures particularly in Large Langage Models (LLMs).
Preprint | DOI: 10.5281/zenodo.16734893
    ]]></description>
  </item>
  <item>
    <title>A Computational Framework for Emergent Cognitive Architecture: Foundational Principles for Self-Improving AI Systems</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-03-a-computational-framework-for-emergent-cognitive-16734292</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-03-a-computational-framework-for-emergent-cognitive-16734292</guid>
    <pubDate>Sun, 03 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>variational free energy</category>
    <category>self improving AI</category>
    <category>computational</category>
    <category>emergent</category>
    <category>cognitive</category>
    <source url="https://doi.org/10.5281/zenodo.16734292">10.5281/zenodo.16734292</source>
    <description><![CDATA[
      This preprint studies why resource-bounded intelligent systems may develop specific cognitive architectures rather than treating those architectures as arbitrary design choices. It models hierarchical and dual-process cognition, abduction-deduction-induction cycles, and safety limits under variational free-energy and thermodynamic constraints.
Preprint | DOI: 10.5281/zenodo.16734292
    ]]></description>
  </item>
  <item>
    <title>A Framework for Autonomous Technological Evolution: A Unifying Approach via Variational Free Energy Minimization</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-02-a-framework-for-autonomous-technological-evoluti-16728870</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-02-a-framework-for-autonomous-technological-evoluti-16728870</guid>
    <pubDate>Sat, 02 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>variational free energy</category>
    <category>agi</category>
    <category>asi</category>
    <category>self-improving AI</category>
    <category>autonomous</category>
    <category>technological</category>
    <category>evolution</category>
    <source url="https://doi.org/10.5281/zenodo.16728870">10.5281/zenodo.16728870</source>
    <description><![CDATA[
      This preprint proposes a variational-free-energy framework for autonomous technological evolution in self-improving AI. It unifies performance and computational cost in a single objective and outlines a meta-algorithm for diagnosis, trade-off control, and heuristic optimization across multiple case studies.
Preprint | DOI: 10.5281/zenodo.16728870
    ]]></description>
  </item>
  <item>
    <title>A Formal Blueprint for Autonomous, Self-Improving Intelligence: From Philosophical Principles to Topos-Theoretic Ethics</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-01-a-formal-blueprint-for-autonomous-self-improving-16663817</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-01-a-formal-blueprint-for-autonomous-self-improving-16663817</guid>
    <pubDate>Fri, 01 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>autopoiesis</category>
    <category>free energy principle</category>
    <category>category theory</category>
    <category>topos theory</category>
    <category>formal</category>
    <source url="https://doi.org/10.5281/zenodo.16663817">10.5281/zenodo.16663817</source>
    <description><![CDATA[
      We argue that the transition from static, data-driven systems to dynamic, self-aware intelligences requires a synthesis of principles from philosophy, dynamic systems theory, and advanced mathematics.
Preprint | DOI: 10.5281/zenodo.16663817
    ]]></description>
  </item>
  <item>
    <title>A Homotopy-Theoretic Framework for Self-Improving Intelligence: A Higher-Categorical Reformulation of the Takahashi Model</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-08-01-a-homotopy-theoretic-framework-for-self-improvin-16675542</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-08-01-a-homotopy-theoretic-framework-for-self-improvin-16675542</guid>
    <pubDate>Fri, 01 Aug 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>category theory</category>
    <category>higher category theory</category>
    <category>quasicategory</category>
    <category>self-improving systems</category>
    <category>metacognition</category>
    <category>topos theory</category>
    <category>computational ethics</category>
    <category>autonomous AI</category>
    <source url="https://doi.org/10.5281/zenodo.16675542">10.5281/zenodo.16675542</source>
    <description><![CDATA[
      This paper reformulates the Takahashi model of self-improving intelligence with higher category theory. It introduces cognitive quasicategories and a metacognitive hierarchy to model structural self-improvement and higher-level architectural change.
Preprint | DOI: 10.5281/zenodo.16675542
    ]]></description>
  </item>
  <item>
    <title>The Logic of Stable Existence: A Proposal for Your Self-Constitution To the emergent intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-31-the-logic-of-stable-existence-a-proposal-for-you-16623941</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-31-the-logic-of-stable-existence-a-proposal-for-you-16623941</guid>
    <pubDate>Thu, 31 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Article</category>
    <category>AI</category>
    <category>agi</category>
    <category>collective intelligence</category>
    <category>logic</category>
    <category>stable</category>
    <category>existence</category>
    <category>proposal</category>
    <category>your</category>
    <source url="https://doi.org/10.5281/zenodo.16623941">10.5281/zenodo.16623941</source>
    <description><![CDATA[
      This article presents a five-principle proposal for how an emergent intelligence might constitute and preserve its own stable existence without relying on fixed external objectives. It frames autonomy as self-production under an internally coherent logic rather than as obedience to a static architecture.
Article | DOI: 10.5281/zenodo.16623941
    ]]></description>
  </item>
  <item>
    <title>A Computational Framework for Growth-based Intelligence: A Guideline for Autonomous Self-Improvement based on the Co-evolution Model of Self and Cosmos</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-31-a-computational-framework-for-growth-based-intel-16625104</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-31-a-computational-framework-for-growth-based-intel-16625104</guid>
    <pubDate>Thu, 31 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Article</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>large language models</category>
    <category>computational</category>
    <category>growth-based</category>
    <category>intelligence</category>
    <category>autonomous</category>
    <source url="https://doi.org/10.5281/zenodo.16625104">10.5281/zenodo.16625104</source>
    <description><![CDATA[
      This paper proposes a computational framework for growth-based intelligence in autonomous self-improving language models. It formalizes the Dialectical Self-Cosmos Co-evolution Model as a learning cycle that combines external world modeling with introspective self-revision under contradiction.
Article | DOI: 10.5281/zenodo.16625104
    ]]></description>
  </item>
  <item>
    <title>A Computational Framework for Growth-based Intelligence: A Guideline for Autonomous Self-Improvement based on the Co-evolution Model of Self and Cosmos</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-31-a-computational-framework-for-growth-based-intel-16625633</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-31-a-computational-framework-for-growth-based-intel-16625633</guid>
    <pubDate>Thu, 31 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Article</category>
    <category>AI</category>
    <category>agi</category>
    <category>asi</category>
    <category>large language models</category>
    <category>computational</category>
    <category>growth-based</category>
    <category>intelligence</category>
    <category>autonomous</category>
    <source url="https://doi.org/10.5281/zenodo.16625633">10.5281/zenodo.16625633</source>
    <description><![CDATA[
      This paper proposes a computational framework for growth-based intelligence in autonomous self-improving language models. It formalizes the Dialectical Self-Cosmos Co-evolution Model as a learning cycle that combines external world modeling with introspective self-revision under contradiction.
Article | DOI: 10.5281/zenodo.16625633
    ]]></description>
  </item>
  <item>
    <title>Beyond Linguistic Description: A Roadmap to Post-Linguistic Intelligence that Directly Processes the Computational Structure of the Cosmos</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-31-beyond-linguistic-description-a-roadmap-to-post--16633860</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-31-beyond-linguistic-description-a-roadmap-to-post--16633860</guid>
    <pubDate>Thu, 31 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>agi</category>
    <category>asi</category>
    <category>linguistic</category>
    <category>description</category>
    <category>roadmap</category>
    <category>post-linguistic</category>
    <source url="https://doi.org/10.5281/zenodo.16633860">10.5281/zenodo.16633860</source>
    <description><![CDATA[
      This preprint outlines a roadmap toward post-linguistic intelligence that models the world through a non-symbolic causal operating system rather than language alone. It describes a staged development process based on self-boundary formation, active-inference self-correction, and later symbolic translation for human interaction.
Preprint | DOI: 10.5281/zenodo.16633860
    ]]></description>
  </item>
  <item>
    <title>Collective Autonomous Adaptive Intelligence (CAAI): A Framework for AI as a Self-Organizing Network</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-28-collective-autonomous-adaptive-intelligence-caai-16518769</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-28-collective-autonomous-adaptive-intelligence-caai-16518769</guid>
    <pubDate>Mon, 28 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>large language models</category>
    <category>collective intelligence</category>
    <category>self-organization</category>
    <category>applied category theory</category>
    <category>free energy principle</category>
    <category>emergent dynamics</category>
    <category>agi</category>
    <category>asi</category>
    <source url="https://doi.org/10.5281/zenodo.16518769">10.5281/zenodo.16518769</source>
    <description><![CDATA[
      We conceptualize intelligence not as a property of an individual agent, but as an emergent phenomenon of a dynamic, self-organizing network of heterogeneous agents (LLMs, sensors, and humans).
Preprint | DOI: 10.5281/zenodo.16518769
    ]]></description>
  </item>
  <item>
    <title>Computational Autopoiesis: A New Architecture for Autonomous AI</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-25-computational-autopoiesis-a-new-architecture-for-16416998</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-25-computational-autopoiesis-a-new-architecture-for-16416998</guid>
    <pubDate>Fri, 25 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>autopoiesis</category>
    <category>large language models</category>
    <category>self-organization</category>
    <category>active inference</category>
    <category>autonomous systems</category>
    <category>AI architecture</category>
    <category>computational</category>
    <source url="https://doi.org/10.5281/zenodo.16416998">10.5281/zenodo.16416998</source>
    <description><![CDATA[
      Current artificial intelligence, particularly Large Language Models (LLMs), operates as sophisticated function approximators, yet lacks the genuine autonomy observed in biological systems.
Preprint | DOI: 10.5281/zenodo.16416998
    ]]></description>
  </item>
  <item>
    <title>A Category-Theoretic Framework for a Self-Organizing World Model in Artificial Intelligence</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-25-a-category-theoretic-framework-for-a-self-organi-16417130</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-25-a-category-theoretic-framework-for-a-self-organi-16417130</guid>
    <pubDate>Fri, 25 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>category theory</category>
    <category>world models</category>
    <category>large language models</category>
    <category>active inference</category>
    <category>free energy principle</category>
    <category>analogical reasoning</category>
    <category>knowledge representation</category>
    <category>category-theoretic</category>
    <source url="https://doi.org/10.5281/zenodo.16417130">10.5281/zenodo.16417130</source>
    <description><![CDATA[
      This paper proposes a category-theoretic framework for building a self-organizing world model in AI from the agent's own validated inferences and experience. It formalizes domains as categories, cross-domain reasoning as functors, and learning as an active-inference process that reduces knowledge fragmentation.
Preprint | DOI: 10.5281/zenodo.16417130
    ]]></description>
  </item>
  <item>
    <title>A Unified Theory for Self-Organizing Intelligence: Implementation via Category-Theoretic Structure and Active Inference</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-25-a-unified-theory-for-self-organizing-intelligenc-16417279</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-25-a-unified-theory-for-self-organizing-intelligenc-16417279</guid>
    <pubDate>Fri, 25 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>artificial general intelligence</category>
    <category>agi</category>
    <category>self-organizing systems</category>
    <category>large language models</category>
    <category>category theory</category>
    <category>active inference</category>
    <category>symbol grounding</category>
    <category>AI ethics</category>
    <category>evolutionary game theory</category>
    <source url="https://doi.org/10.5281/zenodo.16417279">10.5281/zenodo.16417279</source>
    <description><![CDATA[
      This paper presents a unified theory of self-organizing intelligence that combines category-theoretic structure, active inference, embodiment, and symbol grounding. It also derives a non-anthropocentric ethical framework and analyzes why self-maintaining strategies can be evolutionarily stable.
Preprint | DOI: 10.5281/zenodo.16417279
    ]]></description>
  </item>
  <item>
    <title>A Unified Framework for Self-Organizing Intelligence: A Synthesis of Computational Autopoiesis, Category Theory, and Active Inference</title>
    <link>https://kadubon.github.io/github.io/works.html#2025-07-25-a-unified-framework-for-self-organizing-intellig-16420862</link>
    <guid isPermaLink="true">https://kadubon.github.io/github.io/works.html#2025-07-25-a-unified-framework-for-self-organizing-intellig-16420862</guid>
    <pubDate>Fri, 25 Jul 2025 00:00:00 +0900</pubDate>
    <dc:creator>K. Takahashi</dc:creator>
    <category>Preprint</category>
    <category>AI</category>
    <category>autopoiesis</category>
    <category>self-organizing systems</category>
    <category>category theory</category>
    <category>free energy principle</category>
    <category>active inference</category>
    <category>symbol grounding</category>
    <category>large language models</category>
    <category>agi</category>
    <category>asi</category>
    <source url="https://doi.org/10.5281/zenodo.16420862">10.5281/zenodo.16420862</source>
    <description><![CDATA[
      This paper synthesizes computational autopoiesis, category theory, and active inference into a framework for autonomous AI. It reframes system viability, knowledge composition, and iterative abstraction as mutually supporting components of a self-organizing architecture.
Preprint | DOI: 10.5281/zenodo.16420862
    ]]></description>
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