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Surgical affordance maps can now be predicted with unprecedented accuracy, paving the way for true robotic autonomy in complex surgical environments.
Sparse rewards can be transformed into actionable turn-level feedback, enabling agents to learn from both successful and misleading actions in long-horizon tasks.