LLM4SR: A Survey on Large Language Models for Scientific Research
Authors: name: Ziming Luo, name: Zonglin Yang, name: Zexin Xu, name: Wei Yang, name: Xinya Du

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