在这个过程中，测试时强化学习（TTRL）也显得尤为重要。在AI处理复杂数学问题时，TTRL策略能够动态生成更为简单的积分变体，让模型积累经验，帮助其找到解决原问题的方法。与以往单纯增加输出长度的方式不同，TTRL允许模型在推理时进行“刷题”，有效扩展能力边界。

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