Author

Michael G. Rabbat

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Preprint Oct 2026

Cross-Embodiment Robot Foundation World Models with Latent Actions

The diversity of robot embodiments and action spaces makes it challenging to build robot world models that generalize across different embodiments. We introduce the Latent Action-Conditioned Robot World Model (LAC-WM), which operates within a learned unified latent action space shared across diverse embodiments. This u...

Huang Huang, Sriram Yenamandra, Arjun Majumdar et al. · 0 citations

#machine learning Preprint Oct 2026

H-JEPA: End-to-End Learning of Hierarchical World Models for Visual Planning

H-JEPA is introduced, an end-to-end recipe for training a hierarchy of action-conditioned JEPAs in which each level predicts farther ahead in its own learned latent space in which each level's predictions become subgoals for the planner below it.

Wan-Cong Zhang, Basile Terver, Michael G. Rabbat et al. · 4 citations · ⚡2