Putting words into the system’s mouth: A targeted attack on neural machine translation using monolingual data poisoning

Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin Rubinstein, Trevor Cohn


Anthology ID:
2021.findings-acl.127
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1463–1473
Language:
URL:
https://aclanthology.org/2021.findings-acl.127
DOI:
10.18653/v1/2021.findings-acl.127
Bibkey:
Cite (ACL):
Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin Rubinstein, and Trevor Cohn. 2021. Putting words into the system’s mouth: A targeted attack on neural machine translation using monolingual data poisoning. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1463–1473, Online. Association for Computational Linguistics.
Cite (Informal):
Putting words into the system’s mouth: A targeted attack on neural machine translation using monolingual data poisoning (Wang et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-acl.127.pdf
Code
 JunW15/Monolingual-Attack
Data
WikiMatrix