#robot learning

LoopWAM gains 19.7 points on real robots by retraining on its own labeled rollouts

LoopWAM is a closed-loop world-action model from Tsinghua University, Dexmal and Loopeva that scores every rollout by quality and gives failed trajectories video supervision but no action supervision. It ranks first on RoboChallenge's Table30-V2 at 43.33% success, 2.67 points over the VLA-DM0.5 entry in its own table and 0.33 points over the 43.0% Dexmal publishes for DM0.5.