AI RESEARCH
Auditing Frontier Vision-Language Models for Trustworthy Medical VQA: Grounding Failures, Format Collapse, and Domain Adaptation
arXiv CS.AI
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ArXi:2604.27720v1 Announce Type: new Deploying vision-language models (VLMs) in clinical settings demands auditable behavior under realistic failure conditions, yet the failure landscape of frontier VLMs on specialized medical inputs is poorly characterized. We audit five recent frontier and grounding-aware VLMs (Gemini~2.5~Pro, GPT-5, o3, GLM-4.5V, Qwen~2.5~VL) on Medical VQA along two trust-relevant axes.