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KLPO：面向LLM智能体的KL正则策略优化框架
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2026年10月8日，arXiv Machine Learning Theory（一手来源）发表研究，提出KL正则化策略优化（KLPO）框架。该框架将KL正则项锚定在采样器上，使正则化改进步具有闭式Gibbs解，并通过最小二乘拟合对数比最优性条件，从而无需重要性权重。目前报道仅披露上述方法要点，未涉及实验结果、代码开源或后续验证进展。
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Oct 8, 2026
- arXiv · Machine Learning TheoryKL 正则化策略优化研究：提出 KLPO 框架
研究提出 KL 正则化策略优化（KLPO）框架，将 KL 正则项锚定在采样器上，正则化改进步具有闭式 Gibbs 解，并通过最小二乘拟合对数比最优性条件，无需重要性权重。
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