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A small, trainable module can dramatically improve localization accuracy in surgical video analysis, achieving the highest STG score on MedVidBench without retraining existing models.
Achieve robust surgical video question answering by injecting temporal awareness into parameter-efficient fine-tuning, outperforming standard PEFT methods on out-of-template questions.
