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    <abstract>Large language models (LLMs) showcase impressive reasoning capabilities when coupled with Chain-of-Thought (CoT) prompting. However, the robustness of this approach warrants further investigation. In this paper, we introduce a novel scenario termed preemptive answers, where the LLM obtains an answer before engaging in reasoning. This situation can arise inadvertently or induced by malicious users by prompt injection attacks. Experiments reveal that preemptive answers significantly impair the model’s reasoning capability across various CoT methods and a broad spectrum of datasets. To bolster the robustness of reasoning, we propose two measures aimed at mitigating this issue to some extent.</abstract>
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%0 Conference Proceedings
%T Preemptive Answer “Attacks” on Chain-of-Thought Reasoning
%A Xu, Rongwu
%A Qi, Zehan
%A Xu, Wei
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand and virtual meeting
%F xu-etal-2024-preemptive
%X Large language models (LLMs) showcase impressive reasoning capabilities when coupled with Chain-of-Thought (CoT) prompting. However, the robustness of this approach warrants further investigation. In this paper, we introduce a novel scenario termed preemptive answers, where the LLM obtains an answer before engaging in reasoning. This situation can arise inadvertently or induced by malicious users by prompt injection attacks. Experiments reveal that preemptive answers significantly impair the model’s reasoning capability across various CoT methods and a broad spectrum of datasets. To bolster the robustness of reasoning, we propose two measures aimed at mitigating this issue to some extent.
%U https://aclanthology.org/2024.findings-acl.876
%P 14708-14726

Markdown (Informal)

[Preemptive Answer “Attacks” on Chain-of-Thought Reasoning](https://aclanthology.org/2024.findings-acl.876) (Xu et al., Findings 2024)

• Preemptive Answer “Attacks” on Chain-of-Thought Reasoning (Xu et al., Findings 2024)

ACL

• Rongwu Xu, Zehan Qi, and Wei Xu. 2024. Preemptive Answer “Attacks” on Chain-of-Thought Reasoning. In Findings of the Association for Computational Linguistics ACL 2024, pages 14708–14726, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.