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The embodiment gap reveals that even advanced robot foundation models require substantial adaptation to function on specific robotic platforms, challenging the assumption that scaling alone suffices for generalization.
Immediate feedback-driven corrections can enhance robotic manipulation performance without the overhead of retraining entire policies.
Correctable visual attention can drastically enhance robot manipulation performance, especially in unpredictable environments.
