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Co-training generative world models on 1,880 hours of retargeted human motion and video unlocks an 84% real-world humanoid loco-manipulation success rate while drastically slashing the need for costly teleoperated robot data.
Grounding visual dynamics in physical trajectories boosts control success rates by over 24% while reducing prediction drift by nearly 70%.
