A new benchmark and deterministic pipeline translate natural language reasoning into executable Narsese for NARS, with execution-based validation and initial LLM adaptation for three-label classification.
Large language models meet symbolic provers for logical reasoning evaluation
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LogicAgent uses a semiotic-square-guided approach to enhance logical reasoning in LLMs on the new RepublicQA benchmark and others, reporting average gains of 6.25% and 7.05% respectively.
Proposes a three-layer framework using formal AI reasoning for verification, derivation, and discovery in wireless communications theory.
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From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS
A new benchmark and deterministic pipeline translate natural language reasoning into executable Narsese for NARS, with execution-based validation and initial LLM adaptation for three-label classification.
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Semantic-Aware Logical Reasoning via a Semiotic Framework
LogicAgent uses a semiotic-square-guided approach to enhance logical reasoning in LLMs on the new RepublicQA benchmark and others, reporting average gains of 6.25% and 7.05% respectively.
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Rethinking Wireless Communications through Formal Mathematical AI Reasoning
Proposes a three-layer framework using formal AI reasoning for verification, derivation, and discovery in wireless communications theory.