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    <abstract>We investigate the degree to which human (and LLM) plausibility judgments of multiple-choice commonsense benchmark answers are subject to influence by (im)plausibility arguments for or against an answer, in particular, using rationales generated by LLMs. We collect 3,000 plausibility judgments from humans and another 13,600 judgments from LLMs. Overall, we observe increases and decreases in mean human plausibility ratings in the presence of LLM-generated PRO and CON rationales, respectively, suggesting that, on the whole, human judges find these rationales convincing. Experiments with LLMs reveal similar patterns of influence. Our findings demonstrate a novel use of LLMs for studying aspects of human cognition, while also raising practical concerns that, even in domains where humans are “experts” (i.e., common sense), LLMs have the potential to exert considerable influence on people’s beliefs.</abstract>
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%0 Conference Proceedings
%T Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility
%A Palta, Shramay
%A Rankel, Peter A.
%A Wiegreffe, Sarah
%A Rudinger, Rachel
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-390-6
%F palta-etal-2026-arguments
%X We investigate the degree to which human (and LLM) plausibility judgments of multiple-choice commonsense benchmark answers are subject to influence by (im)plausibility arguments for or against an answer, in particular, using rationales generated by LLMs. We collect 3,000 plausibility judgments from humans and another 13,600 judgments from LLMs. Overall, we observe increases and decreases in mean human plausibility ratings in the presence of LLM-generated PRO and CON rationales, respectively, suggesting that, on the whole, human judges find these rationales convincing. Experiments with LLMs reveal similar patterns of influence. Our findings demonstrate a novel use of LLMs for studying aspects of human cognition, while also raising practical concerns that, even in domains where humans are “experts” (i.e., common sense), LLMs have the potential to exert considerable influence on people’s beliefs.
%U https://aclanthology.org/2026.acl-long.599/
%P 13132-13152

Markdown (Informal)

[Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility](https://aclanthology.org/2026.acl-long.599/) (Palta et al., ACL 2026)

• Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility (Palta et al., ACL 2026)

ACL

• Shramay Palta, Peter A. Rankel, Sarah Wiegreffe, and Rachel Rudinger. 2026. Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 13132–13152, San Diego, California, United States. Association for Computational Linguistics.