Better Robustness by More Coverage: Adversarial and Mixup Data Augmentation for Robust Finetuning

Chenglei Si, Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Qun Liu, Maosong Sun


Anthology ID:
2021.findings-acl.137
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:
1569–1576
Language:
URL:
https://aclanthology.org/2021.findings-acl.137
DOI:
10.18653/v1/2021.findings-acl.137
Bibkey:
Cite (ACL):
Chenglei Si, Zhengyan Zhang, Fanchao Qi, Zhiyuan Liu, Yasheng Wang, Qun Liu, and Maosong Sun. 2021. Better Robustness by More Coverage: Adversarial and Mixup Data Augmentation for Robust Finetuning. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1569–1576, Online. Association for Computational Linguistics.
Cite (Informal):
Better Robustness by More Coverage: Adversarial and Mixup Data Augmentation for Robust Finetuning (Si et al., Findings 2021)
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PDF:
https://preview.aclanthology.org/add_acl24_videos/2021.findings-acl.137.pdf
Video:
 https://preview.aclanthology.org/add_acl24_videos/2021.findings-acl.137.mp4
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