AI RESEARCH
Simple Token-Efficient Vision-Language Model for Case-level Pathology Synoptic Report Generation
arXiv CS.AI
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ArXi:2605.30716v1 Announce Type: cross Generating clinically useful pathology reports for pathology cases from whole-slide images (WSIs) is challenging due to gigapixel resolution, long visual-token sequences, and the complexity of case-level reasoning, where a single case may contain multiple WSIs with heterogeneous tissues and ambiguous findings. We present a simple token-efficient vision--language model for case-level synoptic report generation that remains practical under constrained GPU memory.