LLM4SR：大型语言模型在科学研究中的调查。

LLM4SR: A Survey on Large Language Models for Scientific Research

January 8, 2025

作者: Ziming Luo, Zonglin Yang, Zexin Xu, Wei Yang, Xinya Du

cs.AI

摘要

近年来，大型语言模型（LLMs）的快速发展已经彻底改变了科学研究的格局，为研究周期的各个阶段提供了前所未有的支持。本文提出了第一份系统调查报告，专门探讨LLMs如何革新科学研究过程。我们分析了LLMs在研究的四个关键阶段中扮演的独特角色：假设发现、实验规划与实施、科学写作以及同行评审。我们的综述全面展示了任务特定的方法论和评估基准。通过识别当前挑战并提出未来研究方向，这份调查不仅突出了LLMs的变革潜力，还旨在激发和指导研究人员和从业者利用LLMs推动科学探究。资源可在以下存储库获取：https://github.com/du-nlp-lab/LLM4SR。

English

In recent years, the rapid advancement of Large Language Models (LLMs) has transformed the landscape of scientific research, offering unprecedented support across various stages of the research cycle. This paper presents the first systematic survey dedicated to exploring how LLMs are revolutionizing the scientific research process. We analyze the unique roles LLMs play across four critical stages of research: hypothesis discovery, experiment planning and implementation, scientific writing, and peer reviewing. Our review comprehensively showcases the task-specific methodologies and evaluation benchmarks. By identifying current challenges and proposing future research directions, this survey not only highlights the transformative potential of LLMs, but also aims to inspire and guide researchers and practitioners in leveraging LLMs to advance scientific inquiry. Resources are available at the following repository: https://github.com/du-nlp-lab/LLM4SR