Yixiu Mao
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126
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ML×1AI×1
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2026
RLVR without Ineffective Samples: Group Prioritized Off-Policy Optimization for LLM Reasoning
The paper introduces Group Prioritized Off-Policy Optimization (POPO), a novel framework that efficiently accelerates RL finetuning for LLM reasoning by leveraging effective off-policy training batches without requiring costly additional data rollouts.
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Papers
cs.LGcs.AIRecentMay 31, 2026
RLVR without Ineffective Samples: Group Prioritized Off-Policy Optimization for LLM Reasoning
Yixiu Mao, Yun Qu, Qi Wang, Heming Zou +1 more
The paper introduces Group Prioritized Off-Policy Optimization (POPO), a novel framework that efficiently accelerates RL finetuning for LLM reasoning by leveraging effective off-policy training batche…
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