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TDHD boosts surgical manipulation success rates by up to 25% by intelligently adapting action execution based on real-time reliability assessments.
Role-aware evidence routing in surgical video prediction leads to superior performance, demonstrating that asymmetric information exchange can enhance multi-observer models.
EndoWAM achieves real-time, robust navigation in endoscopy by predicting future target regions, outperforming traditional methods in safety-critical settings.
Action precision in autonomous biliary navigation reaches 91.96% by integrating scene-aware learning with instruction conditioning.
GeoCFNet achieves unprecedented accuracy in estimating confidence fields for robot-assisted ESD, crucial for minimizing surgical complications.
