HERB: Measuring hierarchical regional bias in pre-trained language models

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Li, Y., Zhang, G., Yang, B. et al. (4 more authors) (2022) HERB: Measuring hierarchical regional bias in pre-trained language models. In: He, Y., Ji, H., Liu, Y., Li, S. and Chang, C.-H., (eds.) Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022. The 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 20-23 Nov 2022, Online. Association for Computational Linguistics , pp. 334-346. ISBN 9781959429043

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Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • He, Y.
  • Ji, H.
  • Liu, Y.
  • Li, S.
  • Chang, C.-H.
Copyright, Publisher and Additional Information:

© 2022 The Association for Computational Linguistics. Licensed on a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/)

Dates:
  • Published: November 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 05 Jun 2024 15:48
Last Modified: 05 Jun 2024 15:48
Published Version: https://aclanthology.org/2022.findings-aacl.32
Status: Published
Publisher: Association for Computational Linguistics
Refereed: Yes
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