@inproceedings{8a59399e20224fbaa25aa15e093f7571,
title = "Knowledge Navigator: LLM-guided Browsing Framework for Exploratory Search in Scientific Literature",
abstract = "The exponential growth of scientific literature necessitates advanced tools for effective knowledge exploration.We present Knowledge Navigator, a system designed to enhance exploratory search abilities by organizing and structuring the retrieved documents from broad topical queries into a navigable, two-level hierarchy of named and descriptive scientific topics and subtopics.This structured organization provides an overall view of the research themes in a domain, while also enabling iterative search and deeper knowledge discovery within specific subtopics by allowing users to refine their focus and retrieve additional relevant documents.Knowledge Navigator combines LLM capabilities with cluster-based methods to enable an effective browsing method.We demonstrate our approach's effectiveness through automatic and manual evaluations on two novel benchmarks, CLUSTREC-COVID and SCI-TOC.Our code, prompts, and benchmarks are made publicly available.",
author = "Uri Katz and Mosh Levy and Yoav Goldberg",
note = "Publisher Copyright: {\textcopyright} 2024 Association for Computational Linguistics.; 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024 ; Conference date: 12-11-2024 Through 16-11-2024",
year = "2024",
month = jan,
day = "1",
doi = "10.18653/v1/2024.findings-emnlp.516",
language = "American English",
series = "EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024",
publisher = "Association for Computational Linguistics (ACL)",
pages = "8838--8855",
editor = "Yaser Al-Onaizan and Mohit Bansal and Yun-Nung Chen",
booktitle = "EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024",
address = "United States",
}