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Real-world robot failures can be autonomously converted into interactive digital twins for targeted RL, boosting out-of-distribution manipulation by 18.75% while completely bypassing manual teleoperated recovery.
Over 57% of training samples suffer from suppressed criteria, but a new self-distillation method can reverse this trend and enhance performance in RL tasks.
