Author

Ce Hao

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Preprint Aug 2026

LD4WAM: Learning Latent Dynamics from Human Videos for World Action Models

LD4WAM is presented, which pairs a Latent Dynamics Model trained with semantic reconstruction and real motion alignment with a World Dynamics Action Model built as a mixture-of-transformers (MoT), which preserves full future-video generation and uses learnable queries to distill these latent dynamics from generated futures for action conditioning.

Zhen Shen, Jiaqi Liang, Jasper Lu et al. · 0 citations