SOURCE-LINKED INTELLIGENCE
How Identity and Opinion Shape Political Sycophancy in LLMs
As Large Language Models (LLMs) increasingly encourage users to disclose personal profiles for tailored assistance, measuring their political alignment becomes increasingly important. However, many existing benchmarks for assessing political behavior rely on closed-ended questions and do not fully capture how a model's stance may adapt to user-provided context during interaction. We introduce a framework that disentangles two distinct triggers of political sycophancy: opinion (aligning with explicit narratives) and identity (stereotyping based on demographic labels). Using 450 manually-checked
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-29T11:12:03.000Z
First collected: 2026-09-21T07:51:58.603Z. This is not the publication date.