Beyond Logical Forms: LLM-Extracted Patterns for Fallacy Classification
In today's fast-paced information era, logical fallacies, defined as defective patterns of reasoning, inevitably contribute to the growth of information disorder. However, often fallacies appear in nuanced forms that complicate automated classification. In this study, we investigate whether merging abstract logical structures with context-level linguistic cues proves beneficial for fallacy classification, developing a framework that inductively extracts such patterns from fallacious examples and their explanations using Large Language Models (LLMs). We evaluate the impact of these patterns across different LLMs and experimental zero- and one-shot configurations, showing statistically sign...
| Authors | Eleni Papadopulos, Firoj Alam, Giovanni Da San Martino |
|---|---|
| Primary category | cs.CL |
| Published | 25 June 2026 |
| Last updated at source | 25 June 2026 |
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