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Research questionHow can we compare medical VQA models when generation obscures answer signal and biases answer positions?A model may encode information useful for selecting the correct medical answer even when its generated response is unreliable. Generation can also favor particular answer positions, causing comparisons to reflect output behavior rather than medical visual understanding.
AI
Computer Vision
Evaluation & Benchmarks
Health
Machine Learning
Multimodal Models
Latest papersRecent research connected to this question, newest first.MedProb: Probing Internal Representations of Vision-Language Models for Medical Question AnsweringThe evidence covers frozen vision-language model representations for multiple-choice and multiclass Med-VQA on PATH-VQA, SLAKE, and VQA-RAD, including comparisons across general-purpose and medical VLMs, prompting, and agentic systems. The source also reports an open-ended extension using rejection-sampling scoring, but its main results target the multiple-choice setting.research paper · Sep 3, 2026
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