Mitigating Gender Bias in Large Language Models: An Evaluation Using Chain-of-Thought Prompting

Arati Mohapatra, Kavimalar Subbiah, Reshma Sheik, S Jaya Nirmala


Anthology ID:
2024.paclic-1.83
Volume:
Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
Month:
December
Year:
2024
Address:
Tokyo, Japan
Editors:
Nathaniel Oco, Shirley N. Dita, Ariane Macalinga Borlongan, Jong-Bok Kim
Venue:
PACLIC
SIG:
Publisher:
Tokyo University of Foreign Studies
Note:
Pages:
861–870
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URL:
https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.83/
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Cite (ACL):
Arati Mohapatra, Kavimalar Subbiah, Reshma Sheik, and S Jaya Nirmala. 2024. Mitigating Gender Bias in Large Language Models: An Evaluation Using Chain-of-Thought Prompting. In Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation, pages 861–870, Tokyo, Japan. Tokyo University of Foreign Studies.
Cite (Informal):
Mitigating Gender Bias in Large Language Models: An Evaluation Using Chain-of-Thought Prompting (Mohapatra et al., PACLIC 2024)
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https://preview.aclanthology.org/fix-sig-urls/2024.paclic-1.83.pdf