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Reducing visual token exposure by leveraging selective retrieval can dramatically enhance the performance of 3D medical image question answering systems.
EndoVLM achieves superior performance in endoscopic image analysis by effectively aligning clinical reports with visual data, outperforming traditional models and showcasing impressive zero-shot capabilities.
A new unified LVLM, OmniCT, bridges the gap between slice-level detail and volumetric understanding in CT scans, outperforming existing methods by a significant margin.
