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What Should Robot Policies Learn to Predict? Rethinking Supervision Targets in Vision-Language-Action Learning
Vision-language-action (VLA) policies are typically trained with action prediction as the primary supervision signal, since robots ultimately execute actions. Auxiliary objectives such as latent-action (LA) and future-vision (FV) prediction are often added to improve policy learning, yet they compet
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