Unlocking the Unsolvable: Teacher-Guided Curriculum for Data-Efficient RLVR
Reinforcement Learning with Verifiable Rewards (RLVR) has shown remarkable success in improving the mathematical reasoning of large language models. Yet problems beyond the model's current capability, where rollouts uniformly fail and no learning signal is produced, are structurally wasted despite marking the most info...
Yu-Kang Zhu, Zhen-Mao Han
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