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SKL-MAIS, Institute of Automation, Chinese Academy of Sciences, School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing Academy of Artificial Intelligence
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Forget robot-specific fine-tuning: a unified diffusion model can now learn policies across diverse robot embodiments, boosting performance by 15% and opening doors to truly generalizable robotic agents.
Self-play can be dramatically improved by exploiting the "question construction path" it generates as privileged information for self-distillation, leading to 2-3x faster learning.
Zero-shot RL agents can now learn better representations by focusing on dynamics-relevant image regions, leading to state-of-the-art generalization performance.
