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GlanceWAM achieves 72.2% success on RoboCasa while executing actions 24 times faster than traditional synchronous models, reshaping the landscape of real-time robot learning.
Post-training techniques could be the key to overcoming the limitations of traditional imitation learning in autonomous driving, ensuring safer and more reliable vehicle behavior in complex environments.
