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Kuafu's ability to synthesize robust policies from language and task semantics achieves over 82% success in complex manipulation tasks, revolutionizing how we approach control-to-learning paradigms.
RoboEdit transforms abundant human manipulation videos into high-fidelity training data for robots, unlocking new avenues for scalable robot learning.
Counterintuitively, distilling LLMs is more effective when you only use the first few tokens of a student's rollout, surpassing full-trajectory distillation while saving compute.