LLM4SR：關於科學研究中大型語言模型的調查

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

近年來，大型語言模型（LLMs）的快速發展已經改變了科學研究的格局，為研究週期的各個階段提供了前所未有的支持。本文提出了第一份專門探索LLMs如何革新科學研究過程的系統調查。我們分析了LLMs在研究的四個關鍵階段中扮演的獨特角色：假設發現、實驗計劃與實施、科學寫作和同行評審。我們的評論全面展示了任務特定的方法論和評估基準。通過確定當前的挑戰並提出未來的研究方向，這份調查不僅突顯了LLMs的轉型潛力，還旨在激勵和指導研究人員和從業者善用LLMs推動科學探究。相關資源可在以下存儲庫獲得：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