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
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
Bibkey:
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)
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PDF:
https://aclanthology.org/2021.findings-acl.294.pdf
Video:
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