AI RESEARCH
Theory-Grounded Evaluation of Human-Like Fallacy Patterns in LLM Reasoning
arXiv CS.AI
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ArXi:2506.11128v3 Announce Type: replace-cross We study logical reasoning in language models by asking whether their errors follow established human fallacy patterns. Using the Erotetic Theory of Reasoning (ETR) and its open-source implementation, PyETR, we programmatically generate 383 formally specified reasoning problems and evaluate 38 models. For each response, we judge logical correctness and, when incorrect, whether it matches an ETR-predicted fallacy.