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%0 Conference Proceedings
%T AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization
%A Zhang, Xinsong
%A Li, Pengshuai
%A Li, Hang
%Y Zong, Chengqing
%Y Xia, Fei
%Y Li, Wenjie
%Y Navigli, Roberto
%S Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F zhang-etal-2021-ambert
%R 10.18653/v1/2021.findings-acl.37
%U https://aclanthology.org/2021.findings-acl.37
%U https://doi.org/10.18653/v1/2021.findings-acl.37
%P 421-435

Markdown (Informal)

[AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization](https://aclanthology.org/2021.findings-acl.37) (Zhang et al., Findings 2021)

• AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization (Zhang et al., Findings 2021)

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.