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Achieve human-like dexterity in humanoid robots by unifying visual-language cues with learned whole-body proprioceptive dynamics, outperforming prior methods in complex manipulation tasks.
Visual grounding in VLAs weakens in deeper layers, but injecting multi-level visual features and pruning irrelevant tokens can boost performance by 9% in simulation and 7.5% in the real world.