TEXT CAN BE FAIR: Mitigating Popularity Bias with PLMs by Learning Relative Preference.

Zuoli Tang|Zhaoxin Huan|Zihao Li|Shirui Hu|Xiaolu Zhang|Jun Zhou|Lixin Zou|Chenliang Li


Anthology ID:DBLP:conf/cikm/TangHLHZ0ZL24
Volume:Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024
Year:2024
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:2240-2249
URL:https://doi.org/10.1145/3627673.3679581
DOI:https://doi.org/10.1145/3627673.3679581
DBLP:conf/cikm/TangHLHZ0ZL24
BibTeX:
@inproceedings{tang-2024-text, author = {Zuoli Tang and Zhaoxin Huan and Zihao Li and Shirui Hu and Xiaolu Zhang and Jun Zhou and Lixin Zou and Chenliang Li}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{TEXT CAN BE FAIR: Mitigating Popularity Bias with PLMs by Learning Relative Preference}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {2240--2249}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679581}, doi = {https://doi.org/10.1145/3627673.3679581} }