@inproceedings{robbani-etal-2024-flee,
title = "Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling",
author = "Robbani, Irfan and
Reisert, Paul and
Pothong, Surawat and
Inoue, Naoya and
Guerraoui, Cam{\'e}lia and
Wang, Wenzhi and
Naito, Shoichi and
Choi, Jungmin and
Inui, Kentaro",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.1142",
pages = "20524--20540",
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 $\alpha$ 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 and guidelines publicly available.",
}
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<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 and guidelines publicly available.</abstract>
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%0 Conference Proceedings
%T Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling
%A Robbani, Irfan
%A Reisert, Paul
%A Pothong, Surawat
%A Inoue, Naoya
%A Guerraoui, Camélia
%A Wang, Wenzhi
%A Naito, Shoichi
%A Choi, Jungmin
%A Inui, Kentaro
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F robbani-etal-2024-flee
%X 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 and guidelines publicly available.
%U https://aclanthology.org/2024.emnlp-main.1142
%P 20524-20540
Markdown (Informal)
[Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling](https://aclanthology.org/2024.emnlp-main.1142) (Robbani et al., EMNLP 2024)
ACL
- Irfan Robbani, Paul Reisert, Surawat Pothong, Naoya Inoue, Camélia Guerraoui, Wenzhi Wang, Shoichi Naito, Jungmin Choi, and Kentaro Inui. 2024. Flee the Flaw: Annotating the Underlying Logic of Fallacious Arguments Through Templates and Slot-filling. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 20524–20540, Miami, Florida, USA. Association for Computational Linguistics.