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MedVLSynther: Synthesizing High-Quality Visual Question Answering from Medical Documents with Generator-Verifier LMMs

arXiv — cs.LG•Friday, October 31, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
MedVLSynther is a groundbreaking framework that enhances the capabilities of Large Multimodal Models (LMMs) in the medical field by generating high-quality visual question answering (VQA) items from open biomedical literature. This innovation addresses the critical shortage of accessible, high-quality training data for medical VQA systems, enabling better joint reasoning over images and text. By leveraging figures and captions from medical documents, MedVLSynther not only improves the accuracy of medical inquiries but also has the potential to revolutionize how healthcare professionals access and interpret complex information.
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