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About this paper
Choo Sin Wai, Dake Zhong, Jingye Zhang, Zhifang Liu, Siyao Xiao, Zirong Ding, Yuhong Zhang, Kangjie Chen and 5 more
CIALLO learns a shared short-horizon intent space linking robot actions, visual effects, and scene-grounded instructions. It calibrates a new robot’s embodiment parameters from one recording of at most 10 seconds, then freezes the codec during policy training on task demonstrations. On SO-101 and Piper, it averages 76.7% success across six robot-task combinations, versus 70.0% for π0, with task-specific exceptions.
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