How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?

Weijia Xu, Shuming Ma, Dongdong Zhang, Marine Carpuat


Anthology ID:
2021.findings-acl.385
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4392–4400
Language:
URL:
https://aclanthology.org/2021.findings-acl.385
DOI:
10.18653/v1/2021.findings-acl.385
Bibkey:
Cite (ACL):
Weijia Xu, Shuming Ma, Dongdong Zhang, and Marine Carpuat. 2021. How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation?. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 4392–4400, Online. Association for Computational Linguistics.
Cite (Informal):
How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation? (Xu et al., Findings 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.findings-acl.385.pdf
Video:
 https://aclanthology.org/2021.findings-acl.385.mp4
Data
WMT 2014