arXiv AI
Jun 6
Towards an Inferentialist Account of Information Through Proof-theoretic Semantics
arXiv:2605. 05368v4 Announce Type: replace-cross Abstract: Information is one of the most widely-discussed concepts of the current era.
Positive Topology and Feasible Refinement: Forcing Matrices, Positivity, and Information
The paper introduces Positive Topology, a framework built on a basic relation between points (or models) and observable properties. It identifies two complementary structures: universal refinement and cover, and positivity and witnessed existence, showing that each can reconstruct the underlying relation. The authors present both information‑theoretic and game‑theoretic interpretations, and discuss how resource constraints can be integrated, illustrating applications in medical diagnosis, legal reasoning, and AI.
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arXiv AI
Aug 18
Generated Context versus Governed State: Functional Conditions for Accountable Longitudinal Clinical Reasoning
arXiv:2608. 14804v1 Announce Type: new Abstract: Large language models (LLMs) have become the dominant interface of clinical artificial intelligence, yet the interface they expose (text in, text out, one context window at a time) maintains no explicit, persistent, governed representation of what is currently true about a patient.
arXiv AI
Sep 16
Models as Governed Interfaces for AI-Native MBSE: Read-Side Adequacy and Write-Side Admissibility
The paper argues that while machine-readable models like SysML v2 enable AI participation in systems engineering, the data architecture surrounding these models must also be robust. It introduces the concept of epistemic adequacy, split into read‑side adequacy (ensuring derivations, status, and provenance are answerable) and write‑side admissibility (filtering AI contributions before they enter the record). The authors illustrate their ideas using the public Apollo 11 SysML v2 reconstruction and propose a Governed‑Query Architecture Framework to enforce these principles.
arXiv AI
Aug 18
Constitutive Priors for Machine Intelligence: A Legitimacy Theory of the Artificial Physical World
arXiv:2608. 15147v1 Announce Type: new Abstract: Machine intelligence has conquered the symbolic world but stalled at the physical one.
arXiv AI
Jun 2
Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence
arXiv:2606. 01444v1 Announce Type: new Abstract: Scientific discovery is not only answer generation but revision of the representational regime in which evidence, artifacts, operations, and verifiers are typed.
arXiv Computation and Language
Sep 16
Autoformalizing Argumentative Material Inferences
The paper introduces GUARD, a neuro‑symbolic system that autoformalizes argumentative material by completing missing premises (guards) before formal verification. It uses large language models to generate candidate guards, Isabelle/HOL to verify them, and a contrastive test to ensure the proof depends on the original premises and does not over‑generalize. Experiments on Debatepedia and ARCT show that GUARD improves verified‑faithful scores by over 30 points and reduces leakage by about 20 points compared to prior LLM‑driven theorem proving methods.
arXiv AI
Jun 9
Beyond Probabilistic Similarity: Structural, Temporal, and Causal Limitations of Retrieval-Augmented Generation in the Legal Domain
arXiv:2606. 09724v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a standard architectural response to unreliability in legal AI, yet high-profile failures, including fabricated citations submitted to courts and anachronistic legal content presented as current, continue to appear across jurisdictions.
arXiv AI
Aug 28
Knowledge Cards: Structured Knowledge for AI Systems
The paper introduces Knowledge Cards, a new structured artefact designed to capture validated knowledge about specific concepts that AI systems use to make decisions. Unlike existing model, data, and system cards, Knowledge Cards focus on the layer between inputs and outputs, documenting entities, relationships, reasoning patterns, conditions for validity, and provenance, all grounded in a formal domain ontology and signed off by a domain expert. Prototype cards have been created in the energy and pharmaceutical domains, and the schema is released as a public draft for community engagement.
arXiv AI
Aug 21
Causal Reasoning with Bipartite Graphical Causal Models
arXiv:2608. 19831v1 Announce Type: new Abstract: Causal Bayesian networks (CBNs) and structural causal models (SCMs) are the dominant frameworks for graphical causal reasoning, but they cannot adequately represent all real-world causal systems.
arXiv AI
Sep 1
Formal Concept Analysis with Three Types of Negation
arXiv:2608.29311v1 Announce Type: new Abstract: Classic Formal Concept Analysis (FCA) primarily focuses on the positive relationships between objects and attributes and does not have mechanisms for h...
arXiv AI
Jul 9
Neutral Substrates: A Design Constraint for Shared Records Under Persistent Interpretive Disagreement
arXiv:2601. 14271v2 Announce Type: replace Abstract: Shared accountability records are often used by parties who may never agree about causation, responsibility, or normative interpretation.
arXiv AI
Jul 7
The Unverifiability of Artificial General Intelligence (AGI) Alignment, Static and Dynamic: From Trakhtenbrot's Wall to the Safety-Generality Tension
arXiv:2606. 28639v2 Announce Type: replace-cross Abstract: We establish the mathematical limits of AGI safety in two forms: verifying a fixed system, and verifying that a certified safety property persists once the system self-modifies.