AI in Literature Reviews: a survey of current and emerging methods

AI-assisted literature review tools have significantly enhanced researchers' productivity by streamlining the review process and reducing time consumption. Although traditional tools remain widely used, a new generation of tools leveraging state-of-the-art methods, including large language models (LLMs), is gaining popularity. However, LLMs face challenges such as hallucinations, which affect their reliability and accuracy. To address this, solutions such as knowledge augmentation are being explored. Additionally, combining knowledge-augmented LLMs with agentic frameworks has shown promise in improving their performance, making them more reliable and effective for literature review tasks.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/miucc62295.2024.10783597
Citations
3
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
1.04
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article

AI in Literature Reviews: a survey of current and emerging methods

Norehan Mokhtar, Patrick P. Boles, Ghada Khoriba, A. Badr et al.
3 citations
Topic Modeling
1.04
article

AI in Literature Reviews: a survey of current and emerging methods

Norehan Mokhtar, Patrick P. Boles, Ghada Khoriba, A. Badr, Mohamed Saied, Michael E. Adel
article en
3 citations

Abstract

AI-assisted literature review tools have significantly enhanced researchers' productivity by streamlining the review process and reducing time consumption. Although traditional tools remain widely used, a new generation of tools leveraging state-of-the-art methods, including large language models (LLMs), is gaining popularity. However, LLMs face challenges such as hallucinations, which affect their reliability and accuracy. To address this, solutions such as knowledge augmentation are being explored. Additionally, combining knowledge-augmented LLMs with agentic frameworks has shown promise in improving their performance, making them more reliable and effective for literature review tasks.

Nile University (EG)
Openalex Percentile: Top 18%
Topic Modeling
1.04
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