Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification
Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, Kai-Wei Chang
- Anthology ID:
- 2021.findings-acl.294
- Volume:
- Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3320–3331
- Language:
- URL:
- https://aclanthology.org/2021.findings-acl.294
- DOI:
- 10.18653/v1/2021.findings-acl.294
- Cite (ACL):
- Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, and Kai-Wei Chang. 2021. Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3320–3331, Online. Association for Computational Linguistics.
- Cite (Informal):
- Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification (Pruksachatkun et al., Findings 2021)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2021.findings-acl.294.pdf