Knowledge Navigator: LLM-guided Browsing Framework for Exploratory
  Search in Scientific Literature
Authors: name: Uri Katz, name: Mosh Levy, name: Yoav Goldberg

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 SCITOC. Our code,
prompts, and benchmarks are made publicly available.