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TROPIC 论文提出热带强化学习算法

1 reports1 sources16 hr ago updated

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2026年10月5日,arXiv 平台(Artificial Intelligence 期刊,一手来源)发表《Tropical Reinforcement Learning》论文,提出热带强化学习方法。该方法改进大语言模型的组合推理,核心是把传统期望回报中对成功轨迹概率求和改为取最大值,即采用热带半环框架。由此,状态价值被定义为最可能已验证解的对数概率,并保留可重放路径,从而支持跨 rollout 的前缀与后缀组合。目前报道仅涉及论文方法本身,未见后续实验验证或同行评议进展。

Generated from reports · updated 16 hr ago

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Oct 5, 2026
  1. arXiv · Artificial Intelligence
    Tropical Reinforcement Learning:用热带半环改进大语言模型的组合推理

    论文提出 Tropical Reinforcement Learning,把传统期望回报中对成功轨迹概率求和改为取最大值(热带半环),让状态价值等于最可能已验证解的对数概率并保留可重放路径,从而支持跨 rollout 的前缀与后缀组合。

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