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PMTRM: Pseudo-Memory Temporal Re-encoding Module for Embodied Policy Learning
Robotic manipulation often contains repeated motions whose local observations look similar at different phases. When these phases require different actions, a policy that relies mainly on the current observation may repeat completed motions or switch phases at the wrong time. To address this phase a
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