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arxiv:2501.04306

LLM4SR: A Survey on Large Language Models for Scientific Research

Published on Jan 8, 2025

· Submitted by

Zonglin Yang on Jan 9, 2025

Upvote

Authors:

Ziming Luo ,

Zonglin Yang ,

Zexin Xu ,

Wei Yang ,

Xinya Du

Abstract

LLMs are transforming scientific research across hypothesis discovery, experiment planning, writing, and reviewing, offering new methodologies and benchmarks while highlighting challenges for future research.

AI-generated summary

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

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ZonglinY

Paper author Paper submitter Jan 9, 2025

A comprehensive survey on how LLMs can assist the scientific research.
The covered tasks include scientific hypothesis discovery, experiment planning & implementation, paper writing, and paper reviewing.