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SyPS: Measuring Sycophancy Prompt Sensitivity in Large Language Models

arXiv · AI, language, vision and robotics · article · Aug 24, 2026 · UTC

Large language models (LLMs) are known to exhibit social sycophancy, often validating or agreeing with users in socially sensitive contexts. Existing evaluations typically measure sycophancy under a fixed prompt formulation, leaving unclear whether such behavior is stable when the same underlying situation is presented with different sycophancy-relevant prompt variants. In this work, we study sycophancy prompt sensitivity: the extent to which changes in user confidence, emotional framing, social consensus, or validation-seeking language alter a model's sycophantic behavior. We refer to our eva

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Evidence & attribution

First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.