Article

ACT-Flow: Learning Visual Insertion Error Correction with Critic-Weighted Residual Flow

ACT-Flow is an online learning framework that combines an adaptive Action Chunking Transformer (ACT) with a conditional residual flow policy, allowing ACT to absorb successfully executed actions through behavioral cloning, with residual targets recomputed relative to the updated prior.

Part of the event: ACT-Flow proposes an online learning framework for visual insertion

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