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[ICRA 2026] Official implementation of OTAS: Open-vocabulary Token Alignment for Outdoor Segmentation. Training-free language-grounded environment reconstruction and semantic segmentation. Built for in the wild, real-time robotic applications in unstructured and uncooperative environments.
My entry for the AgiBot World Challenge @ ICRA 2026, world model track. GE-Sim 2.0 fine-tuned with a rank-64 LoRA turns one real camera frame plus the robot’s actions into the video of what happens next. Validation score 0.8079.
Imitation-learning policies for the Leju Kuavo humanoid in the Kuavo Data Challenge @ ICRA 2026 (simulation track). ACT trained on 1,000 demos per task across toy sorting, parcel weighing and conveyor sorting: 258.0/300 on local BENCH, top-10 level. Includes training, MuJoCo evaluation harness, results and full reproduction.