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English(EN) AdviSD: Learning to Advise Frontier LLMs via Targeted Multi-Turn Self-Distillation

AdviSD方法通过自蒸馏训练顾问模型来指导LLM

研究人员开发了AdviSD,一种通过自蒸馏训练顾问模型来指导大型语言模型(LLM)的新颖方法。该技术通过选择性地从反馈中学习,即使在纠正不改变执行器即时输出的情况下,也能增强顾问提供有效建议的能力。实验表明,当使用Qwen3_8B顾问指导Gemini和Claude模型在BFCL v3和EnvScaler等基准上运行时,AdviSD的性能显著优于顾问-GRPO等现有方法。训练好的顾问在各种任务和模型家族中表现出泛化能力。 AI

影响 该方法可以提高大型语言模型的可控性和可引导性,从而产生更专业、更高效的AI代理。

排序理由 该集群包含一篇详细介绍AI模型训练新方法的学术论文。

在 arXiv cs.AI 阅读 →

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AdviSD方法通过自蒸馏训练顾问模型来指导LLM

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Rishabh Agrawal, Hejie Cui, Shasha Li, Shanchan Wu, Sercan \"{O}. Ar{\i}k ·

    AdviSD:通过定向多轮自蒸馏学习为前沿大模型提供建议

    arXiv:2609.38142v1 Announce Type: new Abstract: A small trainable advisor can steer a frozen language-model executor using natural-language advice. In addition to learning from task rewards, the advisor can use feedback from completed interactions to improve its advice. However, …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    AdviSD:通过有针对性的多轮自蒸馏学习为前沿大模型提供建议

    A small trainable advisor can steer a frozen language-model executor using natural-language advice. In addition to learning from task rewards, the advisor can use feedback from completed interactions to improve its advice. However, a plausible correction need not change execution…