Papers › Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results

Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results

10 Dec 2019arXiv:1912.04713archive 2025-07-28

Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury

In this paper we look beyond metrics-based evaluation of Information Retrieval systems, to explore the reasons behind ranking results. We present the content-focused Neural-IR-Explorer, which empowers users to browse through retrieval results and inspect the inner workings and fine-grained results of neural re-ranking models. The explorer includes a categorized overview of the available queries, as well as an individual query result view with various options to highlight semantic connections between query-document pairs. The Neural-IR-Explorer is available at: https://neural-ir-explorer.ec.tuwien.ac.at/

PaperPDFCode

Code

sebastian-hofstaetter/neural-ir-explorer officialmentioned in papermentioned on GitHub report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

Information RetrievalRe-RankingRetrieval

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections