RollVerify: Bridging Efficiency and Accuracy in Long-Tail Rollout Reinforcement Learning
Reinforcement learning is crucial for improving large language models'reasoning and generalization. It relies on massive rollouts whose lengths become increasingly long-tailed as context windows grow. In on-policy training, these long-tail rollouts can result in GPU bubbles, reducing system utilization and limiting RL...
Yong-Qiang Yao, Jing-Ru Tan, Kai-Huan Liang et al.
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