Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning
Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g., dVRK) trajectories with synchronized kinematics are costly to collect, while surgical tasks demand precise contact handling, long-horizon reasoning, and bimanual coordination. Endoscopic video is comparatively inexpensive and abundant relative to synchronized video--kinematics trajectories, and a natural way to exploit it is to learn world models o
Record details
Published: 11 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Agents & autonomy
Retrieved: 12 August 2026
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ethics.ai (11 August 2026), “Surgical WAM: A World-Action Model for Data-Efficient Surgical Robot Learning,” evidence record 18648, https://ethics.ai/record/18648 (originally published by arXiv cs.AI).
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