SurgiCLAW: An Interpretable Atomic-Skill Agent for Precision Robotic Micromanipulation

Recent multimodal large language models (MLLMs) and vision--language--action models have provided robots with new capabilities for long-horizon task understanding and planning. In surgical robotics, however, end-to-end prediction of low-level actions remains limited by insufficient precision, opaque decisions, and scarce data.

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