“Reinforcement Learning for Real-Time Vision-Language-Action Policies”

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“Reinforcement Learning for Real-Time Vision-Language-Action Policies” VLA models are usually too slow for reactive robot control, so this paper lets the VLA generate actions slowly in the background, while a lightweight RL policy uses the latest observation to rapidly edit and select actions in real time. This simple split improves real-world success from 42% to 97% with just 10 minutes of online robot data. https://www.alphaxiv.org/abs/2609.18207

Posted by alphaXiv (55.9k followers) 2 h ago · 37 likes · 2k views · view the original post on X. Kept by the AI Radar as AI research. Tools mentioned: alphaXiv.

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