@inproceedings{niu-etal-2026-beyond,
    title = "Beyond Detection: Evaluating Fallacy Awareness of {LLM}s in Interactive Scenarios",
    author = "Niu, Conghui  and
      Wu, Ningxin  and
      Zhao, Ziran  and
      Yu, Dong  and
      Kang, Chen  and
      Liu, Pengyuan",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-long.59/",
    pages = "1331--1352",
    ISBN = "979-8-89176-390-6",
    abstract = "Large Language Models (LLMs) often fail to recognize fallacious reasoning in real-world interactions, despite strong performance on static fallacy detection tasks. We define this ability as \textbf{fallacy awareness}, the capacity to autonomously perceive and resist fallacies in dynamic, pragmatic contexts. To study this, we introduce \textbf{ISFallacy}, a large-scale Chinese benchmark of 50K interactive scenarios spanning six fallacy types, five social interaction settings, diverse role relationships, and personality traits. We further propose \textbf{FATE}, a two-stage evaluation framework that assesses fallacy awareness without explicit cues, combining natural dialogue responses and reasoning-based decisions. Experiments on five representative LLMs reveal a substantial gap between fallacy classification and awareness, with models particularly vulnerable to emotion-driven fallacies and scenarios involving cooperative or trust-based relationships. Deeper analysis uncovers a cognition{--}behavior gap and fragile internal representations underlying awareness failures. Our work establishes a foundation for evaluating and enhancing the robustness of LLMs against fallacious reasoning in interactive settings."
}