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Generative flow matching directly refines 4D hand-object interactions during synthesis, integrating physical constraints and 2D evidence without post-hoc optimization.
HIL-UMI is introduced, a policy-guided Universal Manipulation Interface (UMI) framework for robot-free human-in-the-loop VLA post-training that preserves the iterative and policy-aware nature of human-in-the-loop learning while decoupling data collection from robot deployment.