Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement.
Maryam Mousavian|Zahra Abbasiantaeb|Mohammad Aliannejadi|Fabio Crestani
| Anthology ID: | DBLP:conf/ictir/MousavianAAC25 |
|---|---|
| Volume: | Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025 |
| Year: | 2025 |
| Venue: | International Conference on the Theory of Information Retrieval (ICTIR) |
| Publisher: | ACM |
| Pages: | 56-66 |
| URL: | https://doi.org/10.1145/3731120.3744620 |
| DOI: | https://doi.org/10.1145/3731120.3744620 |
| DBLP: | conf/ictir/MousavianAAC25 |
| BibTeX: |
@inproceedings{mousavian-2025-towards,
author = {Maryam Mousavian and
Zahra Abbasiantaeb and
Mohammad Aliannejadi and
Fabio Crestani},
editor = {Hamed Zamani and
Laura Dietz and
Benjamin Piwowarski and
Sebastian Bruch},
title = {{Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement}},
booktitle = {{Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025}},
pages = {56--66},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3731120.3744620},
doi = {https://doi.org/10.1145/3731120.3744620}
}