English(EN) Prior or Feedback? What an LLM Uses When Adapting Neural Operators

LLM 使用先验知识和反馈来调整神经算子微调

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-09 04:00

一篇新发表在 arXiv 上的研究调查了大型语言模型（LLM）在微调神经算子时如何调整其决策过程。研究人员发现，LLM 同时利用初始的任务相关先验知识，并根据实验反馈进行调整。干预措施表明，LLM 的初始配置很强大，并且当验证分数改变时，后续的提议会发生变化，这表明其对观察到的结果很敏感。 AI

影响这项研究为理解 LLM 如何学习和适应提供了见解，有可能提高它们在科学发现和复杂问题解决方面的能力。

排序理由该集群包含一篇发表在 arXiv 上的研究论文，详细介绍了关于 LLM 适应机制的发现。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

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arXiv cs.AI TIER_1 English(EN) · Julian Chan, Javier Mora Jimenez · 2026-10-09 04:00

先验还是反馈？LLM在适应神经算子时使用什么

arXiv:2610.12325v1 Announce Type: new Abstract: Do LLM scientific agents rely only on their initial task context, or do they adapt their decisions in response to experimental feedback? We study this question in neural operator adaptation, where a large language model (LLM) select…