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Tag: cs.LO
arXiv:2603.23878v1 Announce Type: new Abstract: The parameterized CROWN analysis, a.k.a., alpha-CROWN, has emerged as a practically successful bound propagation method for neural network verification. However, …
arXiv:2603.20405v1 Announce Type: new Abstract: We report on an experiment in which Claude Opus~4.6, equipped with a suite of Model Context Protocol (MCP) tools for …
arXiv:2603.19429v1 Announce Type: new Abstract: Classical planning problems are typically defined using lifted first-order representations, which offer compactness and generality. While most planners ground these …
arXiv:2603.16983v1 Announce Type: new Abstract: Machine learning models for geotechnical hazard prediction can achieve high accuracy while learning physically inconsistent relationships from sparse or biased …
arXiv:2603.13514v1 Announce Type: new Abstract: The Logic Theorist (LT), created by Allen Newell, J. C. Shaw, and Herbert Simon in 1955-1956, is widely regarded as …
arXiv:2603.13574v1 Announce Type: new Abstract: This paper presents a Probabilistic State Algebra as an extension of deterministic propositional logic, providing a computational framework for constructing …
arXiv:2603.12926v1 Announce Type: new Abstract: The ODRL language has become the standard for representing policies and regulations for digital rights. However its complexity is a …
arXiv:2603.06974v1 Announce Type: new Abstract: We present Elenchus, a dialogue system for knowledge base construction grounded in inferentialist semantics, where knowledge engineering is re-conceived as …
arXiv:2603.05562v1 Announce Type: cross Abstract: We consider the problem of modifying a description logic concept in light of models represented as pointed interpretations. We call …
arXiv:2603.03668v1 Announce Type: cross Abstract: Solving constraints involving inductive (aka recursive) definitions is challenging. State-of-the-art SMT/CHC solvers and first-order logic provers provide only limited support …
arXiv:2602.13218v1 Announce Type: new Abstract: Scaling verifiable training signals remains a key bottleneck for Reinforcement Learning from Verifiable Rewards (RLVR). Logical reasoning is a natural …
arXiv:2602.19160v1 Announce Type: new Abstract: This paper examines the reasoning capabilities of Large Language Models (LLMs) from a novel perspective, focusing on their ability to …
