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RLinf-USER: A Unified and Extensible System for Real-World Online Policy Learning in Embodied AI
Online policy learning directly in the physical world is a promising yet challenging direction for embodied intelligence. Unlike simulation, real-world systems cannot be arbitrarily accelerated, cheaply reset, or massively replicated, suggesting that real-world policy learning is not merely an algor
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