LLAssist: Simple Tools for Automating Literature Review Using Large Language Models

Christoforus Yoga Haryanto
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Abstract

This paper introduces LLAssist, an open-source tool designed to streamline literature reviews in academic research. In an era of exponential growth in scientific publications, researchers face mounting challenges in efficiently processing vast volumes of literature. LLAssist addresses this issue by leveraging Large Language Models (LLMs) and Natural Language Processing (NLP) techniques to automate key aspects of the review process. Specifically, it extracts important information from research articles and evaluates their relevance to user-defined research questions. The goal of LLAssist is to significantly reduce the time and effort required for comprehensive literature reviews, allowing researchers to focus more on analyzing and synthesizing information rather than on initial screening tasks. By automating parts of the literature review workflow, LLAssist aims to help researchers manage the growing volume of academic publications more efficiently.
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LLAssist:使用大型语言模型自动进行文献综述的简单工具
本文介绍的 LLAssist 是一款开源工具,旨在简化学术研究中的文献综述。在科学出版物呈指数增长的时代,研究人员在高效处理海量文献方面面临着越来越多的挑战。LLAssist 利用大型语言模型 (LLM) 和自然语言处理 (NLP) 技术,将审稿过程的关键环节自动化,从而解决了这一问题。具体来说,它可以从研究文章中提取重要信息,并评估其与用户定义的研究问题的相关性。LLAssist 的目标是大幅减少综合文献综述所需的时间和精力,让研究人员能够将更多精力放在分析和综合信息上,而不是初步筛选任务上。通过将部分文献综述工作流程自动化,LLAssist 旨在帮助研究人员更高效地管理日益增多的学术出版物。
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