LLAssist: Simple Tools for Automating Literature Review Using Large Language Models
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 8 of its 26 references that are in the map. First posted on arXiv 19 Jul 2024.
Builds on
8 of 26 references.
References · 8
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
- 2020Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performancecited by 396
- 2022Explanations Can Reduce Overreliance on AI Systems During Decision-Makingcited by 111
- 2024LitLLM: A Toolkit for Scientific Literature Reviewcited by 61
- 2014A Comparative Study of Programming Languages in Rosetta Codecited by 19
- 2023PRISMA-DFLLM: An Extension of PRISMA for Systematic Literature Reviews using Domain-specific Finetuned Large Language Modelscited by 8
- 2024Cutting Through the Clutter: The Potential of LLMs for Efficient Filtration in Systematic Literature Reviewscited by 6
Built on by
Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024Automated Review Generation Method Based on Large Language Modelscited by 7
- 2024Contextualized AI for Cyber Defense: An Automated Survey using LLMscited by 1
- 2025Leveraging LLMs for Semi-Automatic Corpus Filtration in Systematic Literature Reviewscited by 1
- 2026Local AI pre-screening for human triple-blind peer review in health sciencescited by 0
- 2026Local AI pre-screening for human triple-blind peer review in health sciences18 Jul 2026
- 2025Leveraging LLMs for Semi-Automatic Corpus Filtration in Systematic Literature Reviews13 Oct 2025
- 2024Contextualized AI for Cyber Defense: An Automated Survey using LLMs20 Sep 2024
- 2024Automated Review Generation Method Based on Large Language Models30 Jul 2024