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Adapting SAM with a hierarchical memory framework boosts surgical instrument segmentation performance beyond existing methods, revealing the critical role of stable category memory in dynamic environments.
LLM-derived preference judgments reveal significant inconsistencies, undermining the reliability of using a single utility function for decision-making.
