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Learning Beyond What You Sample: Off-Policy-Aware Cross-Model Trajectory Exchange for RLVR

Jang, Doohyuk et al.
arXiv (All) · Papers
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artificial-intelligencecomputation-and-languagei-2-6i-2-7machine-learning
Reinforcement Learning with Verifiable Rewards (RLVR) methods such as GRPO rely on successful self-generated trajectories, but finite rollout budgets can produce all-fail groups with no reward-based policy-gradient signal. While additional rollouts improve the chance of success at higher cost, succe
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