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
- Editors:
- Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
- Venue:
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2021.findings-acl.127.pdf
- Code
- JunW15/Monolingual-Attack
- Data
- WikiMatrix