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  <title>MATRIX · OPPD</title>
  <link>https://derekwang2002.github.io/ai-intelligence/projects/oppd/</link>
  <description>AI 模型、Agent、工程与基础设施的重要变化，附一手来源与建议等级。</description>
  <language>zh-CN</language>
  <lastBuildDate>Mon, 02 Nov 2026 16:56:00 GMT</lastBuildDate>
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    <title>OPPD 把昂贵的答案搜索蒸馏进一次生成</title>
    <link>https://derekwang2002.github.io/ai-intelligence/events/ev-20261005-05/</link>
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    <pubDate>Tue, 06 Oct 2026 16:01:24 GMT</pubDate>
    <category>新事件</category>
    <category>TRIAL</category>
    <description>&lt;p&gt;On-policy power distillation（OPPD）让模型用一次生成逼近经过锐化的整段答案分布。冻结的教师模型为序贯蒙特卡洛产生的候选答案加权，再用这些权重训练学生，不需要参考答案。作者报告相对基础 checkpoint 在 MATH-500 上最高提升 23 点、GSM8K 上提升 27.3 点，并在相同预算下超过 GRPO。代码已公开。&lt;/p&gt;&lt;p&gt;建议等级：TRIAL&lt;/p&gt;&lt;p&gt;来源：&lt;a href=&quot;https://arxiv.org/abs/2610.06804&quot;&gt;Sharpen Without Search: OPPD&lt;/a&gt; · &lt;a href=&quot;https://github.com/ArminAzizi98/OPPD&quot;&gt;ArminAzizi98/OPPD&lt;/a&gt;&lt;/p&gt;</description>
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