@inproceedings{bao-etal-2021-defending,
title = "Defending Pre-trained Language Models from Adversarial Word Substitution Without Performance Sacrifice",
author = "Bao, Rongzhou and
Wang, Jiayi and
Zhao, Hai",
editor = "Zong, Chengqing and
Xia, Fei and
Li, Wenjie and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.287/",
doi = "10.18653/v1/2021.findings-acl.287",
pages = "3248--3258"
}
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%0 Conference Proceedings
%T Defending Pre-trained Language Models from Adversarial Word Substitution Without Performance Sacrifice
%A Bao, Rongzhou
%A Wang, Jiayi
%A Zhao, Hai
%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 bao-etal-2021-defending
%R 10.18653/v1/2021.findings-acl.287
%U https://aclanthology.org/2021.findings-acl.287/
%U https://doi.org/10.18653/v1/2021.findings-acl.287
%P 3248-3258
Markdown (Informal)
[Defending Pre-trained Language Models from Adversarial Word Substitution Without Performance Sacrifice](https://aclanthology.org/2021.findings-acl.287/) (Bao et al., Findings 2021)
ACL