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A single GPU can now plan complex, contact-rich robotic manipulation trajectories for thousands of parallel worlds, achieving near-80% success on challenging in-hand rotation tasks with unprecedented speed.
A novel "Predictive Intent" token bridges VLMs and VGMs for robot manipulation, unlocking superior out-of-distribution generalization without embodied pretraining.
HumanScore reveals that traditional kinematic metrics overlook critical failures in humanoid motion tracking, such as unstable support and incorrect contacts.
Training with just 3% of high-quality motion data can yield superior tracking performance compared to using the entire dataset.