Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling
Irfan Robbani, Paul Reisert, Surawat Pothong, Naoya Inoue, Camélia Guerraoui, Wenzhi Wang, Shoichi Naito, Jungmin Choi, Kentaro Inui
Abstract
Prior research in computational argumentation has mainly focused on scoring the quality of arguments, with less attention on explicating logical errors. In this work, we introduce four sets of explainable templates for common informal logical fallacies designed to explicate a fallacy's implicit logic. Using our templates, we conduct an annotation study on top of 400 fallacious arguments taken from LOGIC dataset and achieve a high agreement score (Krippendorf's α of 0.54) and reasonable coverage 83%. Finally, we conduct an experiment for detecting the structure of fallacies and discover that state-of-the-art language models struggle with detecting fallacy templates (0.47 accuracy). To facilitate research on fallacies, we make our dataset, guidelines, and code publicly available.
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Cited by top-tier papers2
- Truth or Sophistry? LoFa: A Benchmark for LLM Robustness Against Logical FallaciesXudong Shen, Li Yuan, Ye Chen, Xin Wu et al.ACL 2026
- Identification of Multiple Logical Interpretations in Counter-ArgumentsWenzhi Wang, Paul Reisert, Shoichi Naito, Naoya Inoue et al.EMNLP 2025
Builds on3
- Multitask Instruction-based Prompting for Fallacy RecognitionTariq Alhindi, Tuhin Chakrabarty, Elena Musi, Smaranda MuresanEMNLP 2022 · 16 citations
- Argument-based Detection and Classification of Fallacies in Political DebatesPierpaolo Goffredo, Mariana Espinoza, Serena Villata, Elena CabrioEMNLP 2023 · 4 citations
- Breaking Down the Invisible Wall of Informal Fallacies in Online DiscussionsSaumya Sahai, Oana Balalau, Roxana HorincarACL 2021
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