<ul><li>Large Language Models (LLMs) have improved our ability to process complex language, but detecting logical fallacies remains a challenge.</li><li>A study introduces a novel prompt formulation approach for logical fallacy detection.</li><li>The approach incorporates counterarguments, explanations, and goals to enrich the input text.</li><li>The method shows substantial improvements over previous models in both supervised and unsupervised settings.</li></ul>

Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation

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