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CLAP achieves zero-shot deployment of physical simulators across diverse robot embodiments, outperforming traditional models in complex environments.
Robots can now learn better world models through unsupervised self-play, outperforming models trained on human data by 40% in failure prediction and 65% in real-world RL.
