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Conformal Prediction-Enabled Sequence-level Policy Optimization for Reasoning Language Models
Reinforcement learning improves the reasoning capability of large language models through verifiable rewards for mathematical and coding tasks. In token-level methods such as GRPO, clipping acts on individual token ratios while the reward and advantage apply to a complete response. Recent sequence-l
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