GEAR-Up: Generative AI and External Knowledge-Based Retrieval: Upgrading Scholarly Article Searches for Systematic Reviews

Authors

  • Kaushik Roy AI Institute, University of South Carolina
  • Vedant Khandelwal AI Institute, University of South Carolina
  • Valerie Vera University Libraries, University of South Carolina
  • Harshul Surana AI Institute, University of South Carolina
  • Heather Heckman University Libraries, University of South Carolina
  • Amit Sheth AI Institute, University of South Carolina

DOI:

https://doi.org/10.1609/aaai.v38i21.30577

Keywords:

Artificial Intelligence

Abstract

This paper addresses the time-intensive nature of systematic reviews (SRs) and proposes a solution leveraging advancements in Generative AI (e.g., ChatGPT) and external knowledge augmentation (e.g., Retrieval-Augmented Generation). The proposed system, GEAR-Up, automates query development and translation in SRs, enhancing efficiency by enriching user queries with context from language models and knowledge graphs. Collaborating with librarians, qualitative evaluations demonstrate improved reproducibility and search strategy quality. Access the demo at https://youtu.be/zMdP56GJ9mU.
AAAI-24 / IAAI-24 / EAAI-24 Proceedings Cover

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Published

2024-03-24

How to Cite

Roy, K., Khandelwal, V., Vera, V., Surana, H., Heckman, H., & Sheth, A. (2024). GEAR-Up: Generative AI and External Knowledge-Based Retrieval: Upgrading Scholarly Article Searches for Systematic Reviews. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23823–23825. https://doi.org/10.1609/aaai.v38i21.30577

Issue

Vol. 38 No. 21: IAAI-24, EAAI-24, AAAI-24 Student Abstracts, Undergraduate Consortium and Demonstrations

Section

AAAI Demonstration Track