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Explicitly supervising physical state changes, not just language or latent representations, unlocks more robust VLA model generalization and real-world robotic control.
A VLA system achieves 92.9% success on physical object transfers in additive manufacturing by chunking actions and using closed-loop feedback between open-loop execution.