Good Arguments Against the People Pleasers: How Reasoning Mitigates (Yet Masks) LLM Sycophancy

Zhaoxin Feng, Zheng Chen, Jianfei Ma, Yip Tin Po, Emmanuele Chersoni +1 more
3/17/2026
cs.CL

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Abstract

Alignment techniques often inadvertently induce sycophancy in LLMs. While prior studies studied this behaviour in direct-answer settings, the role of Chain-of-Thought (CoT) reasoning remains under-explored: does it serve as a logical constraint that mitigates sycophancy, or a tool for post-hoc rationalization that masks it? We evaluate a range of models across objective and subjective tasks to investigate the issue. Results show that reasoning generally reduces sycophancy in final decisions but also masks sycophancy in some samples, where models construct deceptive justifications through logical inconsistencies, calculation errors, and one-sided arguments etc. Furthermore, LLMs are more prone to sycophancy in subjective tasks and under authority-bias. Our mechanistic analysis on three open-source models reveals that the tendency of sycophancy is dynamic during the reasoning process rather than being pre-determined at the input stage.

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Cite this paper

@article{feng2026good,
  title  = {Good Arguments Against the People Pleasers: How Reasoning Mitigates (Yet Masks) LLM Sycophancy},
  author = {Zhaoxin Feng and Zheng Chen and Jianfei Ma and Yip Tin Po and Emmanuele Chersoni and Bo Li},
  year   = {2026},
  eprint = {2603.16643},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2603.16643v1}
}

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