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Existing VLMs misinterpret critical evidence in exploratory manipulation, but a novel distillation approach boosts action recovery accuracy by nearly half.
Robot RL training can be dramatically sped up (3-10x) by decoupling CPU-based simulation from GPU-based learning, challenging the assumption that GPU-resident physics is essential for efficiency.
