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Why is action chunking so important for robot behavior cloning? Even when open-loop execution reduces the policy’s reactivity? 🤖 Our latest work identifies the most important reason: **action chunking helps short-memory policies imitate long-memory experts**. More precisely,
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Action chunking — especially executing long action sequences open-loop — is widely used in imitation learning for robotic manipulation. Why is it so effective and do we really need it? We find a key reason:
Long open-loop execution helps short-context policies imitate
