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Transforming static clinical cases into interactive storytelling games, MedGame significantly enhances engagement and learning outcomes in medical education.
Surgical affordance maps can now be predicted with unprecedented accuracy, paving the way for true robotic autonomy in complex surgical environments.
Continuous and consistent robotic actions can be achieved without additional network parameters, revolutionizing how robots interpret and execute complex tasks.
A simple change in the source distribution can boost generative robot policy success rates by over 25%.
Synthetic data can overcome data scarcity and textureless challenges to enable surprisingly accurate surgical instrument pose estimation from RGB images alone.
Force your VLMs to *show their work*: Saliency-R1 aligns model attention with human-annotated visual cues, boosting faithfulness and interpretability without extra compute.
Surgical AI gets a major data boost: Surg$危$ unifies millions of surgical conversations with multimodal annotations, paving the way for more generalizable and interpretable models.
