为了提高覆盖率，采用了一种简单的策略：对于16轮MCTS回合后仍未解决的问题，增加执行64轮回合，必要时增至128轮。并对不同随机种子进行多次MCTS扩展。成功将奥林匹克级问题的成功率提高至80.58%。

今天登顶 Hugging Face 热门榜一的论文展示了小模型的潜力。来自微软亚洲研究院的研究团队提出了 rStar-Math 。rStar-Math 向我们证明，1.5B 到 7B ...

小声说，微软最近有一股在小·大模型 圈子里重拳出击的态势：昨天刚开源了目前最强的小·大模型，14B的phi-4；今天又推出了rStar-Math，论文中直指其面向小语言模型 （SLM） 。

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