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RLT: Teaching a frozen VLA the last few millimeters with online reinforcement learning

RLT proposes freezing the large VLA model and training only a lightweight actor-critic control head: the VLA handles visual and language understanding and coarse actions, while the small network corrects actions online during critical stages to make up the last few millimeters of precision. The two are connected through a bridging structure.

Part of the event: RLT proposes an online reinforcement learning approach that freezes VLA and trains only the control head

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