The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification

Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang


Anthology ID:
2021.findings-acl.7
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:
74–85
Language:
URL:
https://aclanthology.org/2021.findings-acl.7
DOI:
10.18653/v1/2021.findings-acl.7
Bibkey:
Cite (ACL):
Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, and Jiliang Tang. 2021. The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 74–85, Online. Association for Computational Linguistics.
Cite (Informal):
The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification (Liu et al., Findings 2021)
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PDF:
https://aclanthology.org/2021.findings-acl.7.pdf
Video:
 https://aclanthology.org/2021.findings-acl.7.mp4