ExpandFuse: A Hybrid Retrieval Framework with Query Expansion and Topic-Aware Reranking for Multi-Hop Question Answering

No full text

Paper published on a website (Scientific congresses, symposiums and conference proceedings)

MURUGARAJ, Keerthana; LAMSIYAH, Salima; THEOBALD, Martin

2025 • 13th IEEE International Conference on Big Data (IEEE BigData 2025)

Peer reviewed

Permalink
https://hdl.handle.net/10993/67971

DOI
10.1109/bigdata66926.2025.11402490

No document available.

Disciplines :

Computer science

Author, co-author :

MURUGARAJ, Keerthana ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

LAMSIYAH, Salima ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

THEOBALD, Martin ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)

External co-authors :

Language :

English

Title :

ExpandFuse: A Hybrid Retrieval Framework with Query Expansion and Topic-Aware Reranking for Multi-Hop Question Answering

Publication date :

08 December 2025

Event name :

13th IEEE International Conference on Big Data (IEEE BigData 2025)

Event date :

8-11 December, 2025

Peer reviewed :

Peer reviewed

Source :

Additional URL :

Available on ORBilu :

since 10 March 2026

Number of views

36 (1 by Unilu)

Number of downloads

0 (0 by Unilu)

OpenAlex citations