AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization

Xinsong Zhang, Pengshuai Li, Hang Li


Anthology ID:
2021.findings-acl.37
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:
421–435
Language:
URL:
https://aclanthology.org/2021.findings-acl.37
DOI:
10.18653/v1/2021.findings-acl.37
Bibkey:
Cite (ACL):
Xinsong Zhang, Pengshuai Li, and Hang Li. 2021. AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 421–435, Online. Association for Computational Linguistics.
Cite (Informal):
AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization (Zhang et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-acl.37.pdf
Video:
 https://aclanthology.org/2021.findings-acl.37.mp4
Data
CLUECMNLICMRCCMRC 2018ChIDCoLAGLUEMRPCMultiNLIQNLISSTSST-2