SOURCE-LINKED INTELLIGENCE
SyPS: Measuring Sycophancy Prompt Sensitivity in Large Language Models
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
- arXiv · AI, language, vision and robotics · 2026-08-24T21:24:50.000Z
First collected: 2026-09-21T10:22:00.206Z. This is not the publication date.