由此诞生了强化学习与可验证奖励（Reinforcement Learning with Verifiable Rewards，简称RLVR）。各种RLVR算法层出不穷，但都面临着一个致命的弱点——模型太容易“早熟”了，也就是过早收敛，并且训练过程中还会出现一种叫“熵崩溃”的现象，也就是模型的思想僵化了，失去了探索新世界的动力。

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