JEPA-WAM couples latent transition prediction in a frozen V-JEPA space with action generation through a shared predictor, improving out-of-distribution manipulation success on LIBERO-Plus, RoboTwin 2.0, and a real bimanual robot.
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JEPA-WAM: Learning Vision-Language-Action Policies with Joint-Embedding World Modeling
JEPA-WAM couples latent transition prediction in a frozen V-JEPA space with action generation through a shared predictor, improving out-of-distribution manipulation success on LIBERO-Plus, RoboTwin 2.0, and a real bimanual robot.