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Diversifying RLVR Rollouts via First-Token Exploration

Kim, Soeun et al.
arXiv (All) · Papers
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computation-and-language
Reinforcement learning with verifiable rewards (RLVR) trains reasoning models without labeled trajectories, using groups of verifier-scored rollouts to explore alternative reasoning paths. Limited rollout diversity is a central bottleneck, typically addressed through adjustments to temperature, pref
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