CRAFT is a unified bidirectional counterfactual reasoning framework that improves LLM performance on tabular QA and fact verification tasks over baselines on WikiTQ and TabFact.
Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation
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LLM-extracted patterns merging logical structures and linguistic cues yield statistically significant gains in fallacy classification over zero-shot baselines with cross-dataset generalization.
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CRAFT: A Unified Counterfactual Reasoning Framework for Tabular Question Answering and Fact Verification
CRAFT is a unified bidirectional counterfactual reasoning framework that improves LLM performance on tabular QA and fact verification tasks over baselines on WikiTQ and TabFact.
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Beyond Logical Forms: LLM-Extracted Patterns for Fallacy Classification
LLM-extracted patterns merging logical structures and linguistic cues yield statistically significant gains in fallacy classification over zero-shot baselines with cross-dataset generalization.