Causal-ACT masks task-irrelevant image features and lifts out-of-distribution transfer success from 0.23 to 0.82 in a simulated ALOHA cube transfer task.
Sim-to-real transfer for vision-and-language navigation
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Improving Generalization Ability of Robotic Imitation Learning by Resolving Causal Confusion in Observations
Causal-ACT masks task-irrelevant image features and lifts out-of-distribution transfer success from 0.23 to 0.82 in a simulated ALOHA cube transfer task.