@inproceedings{han-etal-2021-decoupling,
title = "Decoupling Adversarial Training for Fair {NLP}",
author = "Han, Xudong and
Baldwin, Timothy and
Cohn, Trevor",
editor = "Zong, Chengqing and
Xia, Fei and
Li, Wenjie and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2021.findings-acl.41/",
doi = "10.18653/v1/2021.findings-acl.41",
pages = "471--477"
}
Markdown (Informal)
[Decoupling Adversarial Training for Fair NLP](https://preview.aclanthology.org/add-emnlp-2024-awards/2021.findings-acl.41/) (Han et al., Findings 2021)
ACL
- Xudong Han, Timothy Baldwin, and Trevor Cohn. 2021. Decoupling Adversarial Training for Fair NLP. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 471–477, Online. Association for Computational Linguistics.