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

Long-horizon planning with latent world models requires reasoning across timescales and levels of abstraction. Existing task-agnostic JEPA world models predict and plan at a single timescale or with multiple horizons in one shared latent space. We introduce H-JEPA, an end-to-end recipe for training a hierarchy of actio...

Wan-Cong Zhang, Basile Terver, Michael G. Rabbat et al. · 0 citations