FairWork: A Generic Framework For Evaluating Fairness In LLM-Based Job Recommender System.

Teng Guo|Yuhan Hu|Mi Tian|Ziyu Lyu|Lu Bai|Teng Guo|Yuhan Hu|Lixin Cui|Zitao Liu|Mi Tian|Ziyu Lyu|Lixin Cui|Zitao Liu


Anthology ID:DBLP:conf/sigir/HuL0C25
Volume:Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025
Year:2025
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:3964-3968
URL:https://doi.org/10.1145/3726302.3730145
DOI:https://doi.org/10.1145/3726302.3730145
DBLP:conf/sigir/HuL0C25
BibTeX:
@inproceedings{guo-2025-fairwork, author = {Teng Guo and Yuhan Hu and Mi Tian and Ziyu Lyu and Lu Bai and Teng Guo and Yuhan Hu and Lixin Cui and Zitao Liu and Mi Tian and Ziyu Lyu and Lixin Cui and Zitao Liu}, editor = {Nicola Ferro and Maria Maistro and Gabriella Pasi and Omar Alonso and Andrew Trotman and Suzan Verberne}, title = {{FairWork: A Generic Framework For Evaluating Fairness In LLM-Based Job Recommender System}}, booktitle = {{Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025}}, pages = {3964--3968}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3726302.3730145}, doi = {https://doi.org/10.1145/3726302.3730145} }