SQuAI: Scientific Question-Answering with Multi-Agent Retrieval-Augmented Generation.
Ines Besrour|Jingbo He|Tobias Schreieder|Michael Färber
| Anthology ID: | DBLP:conf/cikm/BesrourHS025 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 6603-6608 |
| URL: | https://doi.org/10.1145/3746252.3761471 |
| DOI: | https://doi.org/10.1145/3746252.3761471 |
| DBLP: | conf/cikm/BesrourHS025 |
| BibTeX: |
@inproceedings{besrour-2025-squai,
author = {Ines Besrour and
Jingbo He and
Tobias Schreieder and
Michael F\"{a}rber},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{SQuAI: Scientific Question-Answering with Multi-Agent Retrieval-Augmented Generation}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {6603--6608},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761471},
doi = {https://doi.org/10.1145/3746252.3761471}
}