LLM4SR: A Survey on Large Language Models for Scientific Research
It provides a comprehensive overview for researchers and practitioners to leverage LLMs in advancing scientific inquiry, but it is incremental as a survey paper.
This paper presents the first systematic survey on how Large Language Models (LLMs) are transforming scientific research by analyzing their roles in hypothesis discovery, experiment planning, scientific writing, and peer reviewing, and it identifies challenges and future directions to guide researchers.
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