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
Latent world models have shown a remarkable ability to predict future states and to plan in the real world. In practice, however, we lack a principled way to estimate how their capabilities scale with model size, data, and compute, an open problem that slows progress in the field. In this work we present RoboJEPA, a wo...
Artem Zholus, Nicolas Beltran-Velez, Jian-Hao Yuan et al.· 0 citations
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