AI RESEARCH
PathMem: Toward Cognition-Aligned Memory Transformation for Pathology MLLMs
arXiv CS.AI
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ArXi:2603.09943v1 Announce Type: new Computational pathology demands both visual pattern recognition and dynamic integration of structured domain knowledge, including taxonomy, grading criteria, and clinical evidence. In practice, diagnostic reasoning requires linking morphological evidence with formal diagnostic and grading criteria. Although multimodal large language models (MLLMs) nstrate strong vision language reasoning capabilities, they lack explicit mechanisms for structured knowledge integration and interpretable memory control.