Do Multimodal LLMs See Before They Read? Diagnosing Contextual Sycophancy
External text can override conflicting image evidence in multimodal large language models, a failure we call multimodal contextual sycophancy. We introduce a 998-case diagnostic that independently varies visual evidence, commonsense priors, and external text, and probe when this failure arises by moving the information boundary around a context-blind visual witness. On abnormal images paired with Gemini-generated false text, GPT-5.1 scores 7.9% under joint conditioning, 49.7% when the context-blind witness report is scored directly, 63.7% under a matched two-call witness-arbiter pipeline that exposes the witness to the text, and 84.2% under System-2 Visual Arbitration (S2VA), which withho...
| Authors | Yi-Cheng Lai, Hen-Hsen Huang |
|---|---|
| Primary category | cs.CL |
| Published | 30 August 2026 |
| Last updated at source | 10 September 2026 |
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