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ADAPT enables humanoid robots to seamlessly execute diverse motion skills in real-time based on text commands, revolutionizing interactive control.
By refining VLM-derived reward signals with structural priors, SAFT transforms noisy feedback into a reliable guide for faster and more aligned policy learning.
HarnessCompass boosts agent performance by 22% in just five iterations, setting a new standard for generalization in automatic harness evolution.
A groundbreaking dataset of 4D human motion sequences reveals how humanoid robots can effectively navigate complex terrains, setting a new standard for motion synthesis accuracy.
