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Joint online post-training in GenTrack boosts humanoid tracking accuracy and expands zero-shot capabilities without requiring new data.
A surprisingly simple change to the motion latent space—representing each body joint with its own token—dramatically improves text-to-motion generation quality, outperforming monolithic latent vector approaches.