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Video-derived geometric supervision enables a 33% reduction in collisions and a 150% increase in navigation success for VLAs, reshaping the landscape of obstacle-aware navigation.
Counterfactual human preference labels dramatically improve robot navigation safety, reducing collisions by nearly 50% in simulation and boosting real-world goal success by 24%.
