The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21
Lihua Qian, Yi Zhou, Zaixiang Zheng, Yaoming Zhu, Zehui Lin, Jiangtao Feng, Shanbo Cheng, Lei Li, Mingxuan Wang, Hao Zhou
Abstract
This paper describes the Volctrans’ submission to the WMT21 news translation shared task for German->English translation. We build a parallel (i.e., non-autoregressive) translation system using the Glancing Transformer, which enables fast and accurate parallel decoding in contrast to the currently prevailing autoregressive models. To the best of our knowledge, this is the first parallel translation system that can be scaled to such a practical scenario like WMT competition. More importantly, our parallel translation system achieves the best BLEU score (35.0) on German->English translation task, outperforming all strong autoregressive counterparts.- Anthology ID:
- 2021.wmt-1.17
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 187–196
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.17
- DOI:
- Bibkey:
- Cite (ACL):
- Lihua Qian, Yi Zhou, Zaixiang Zheng, Yaoming Zhu, Zehui Lin, Jiangtao Feng, Shanbo Cheng, Lei Li, Mingxuan Wang, and Hao Zhou. 2021. The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21. In Proceedings of the Sixth Conference on Machine Translation, pages 187–196, Online. Association for Computational Linguistics.
- Cite (Informal):
- The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21 (Qian et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.17.pdf
Export citation
@inproceedings{qian-etal-2021-volctrans,
title = "The Volctrans {GLAT} System: Non-autoregressive Translation Meets {WMT}21",
author = "Qian, Lihua and
Zhou, Yi and
Zheng, Zaixiang and
Zhu, Yaoming and
Lin, Zehui and
Feng, Jiangtao and
Cheng, Shanbo and
Li, Lei and
Wang, Mingxuan and
Zhou, Hao",
editor = "Barrault, Loic and
Bojar, Ondrej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-jussa, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Freitag, Markus and
Graham, Yvette and
Grundkiewicz, Roman and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Kocmi, Tom and
Martins, Andre and
Morishita, Makoto and
Monz, Christof",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.17",
pages = "187--196",
abstract = "This paper describes the Volctrans{'} submission to the WMT21 news translation shared task for German-{\textgreater}English translation. We build a parallel (i.e., non-autoregressive) translation system using the Glancing Transformer, which enables fast and accurate parallel decoding in contrast to the currently prevailing autoregressive models. To the best of our knowledge, this is the first parallel translation system that can be scaled to such a practical scenario like WMT competition. More importantly, our parallel translation system achieves the best BLEU score (35.0) on German-{\textgreater}English translation task, outperforming all strong autoregressive counterparts.",
}
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%0 Conference Proceedings %T The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21 %A Qian, Lihua %A Zhou, Yi %A Zheng, Zaixiang %A Zhu, Yaoming %A Lin, Zehui %A Feng, Jiangtao %A Cheng, Shanbo %A Li, Lei %A Wang, Mingxuan %A Zhou, Hao %Y Barrault, Loic %Y Bojar, Ondrej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussa, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Kocmi, Tom %Y Martins, Andre %Y Morishita, Makoto %Y Monz, Christof %S Proceedings of the Sixth Conference on Machine Translation %D 2021 %8 November %I Association for Computational Linguistics %C Online %F qian-etal-2021-volctrans %X This paper describes the Volctrans’ submission to the WMT21 news translation shared task for German-\textgreaterEnglish translation. We build a parallel (i.e., non-autoregressive) translation system using the Glancing Transformer, which enables fast and accurate parallel decoding in contrast to the currently prevailing autoregressive models. To the best of our knowledge, this is the first parallel translation system that can be scaled to such a practical scenario like WMT competition. More importantly, our parallel translation system achieves the best BLEU score (35.0) on German-\textgreaterEnglish translation task, outperforming all strong autoregressive counterparts. %U https://aclanthology.org/2021.wmt-1.17 %P 187-196
Markdown (Informal)
[The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21](https://aclanthology.org/2021.wmt-1.17) (Qian et al., WMT 2021)
- The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21 (Qian et al., WMT 2021)
ACL
- Lihua Qian, Yi Zhou, Zaixiang Zheng, Yaoming Zhu, Zehui Lin, Jiangtao Feng, Shanbo Cheng, Lei Li, Mingxuan Wang, and Hao Zhou. 2021. The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21. In Proceedings of the Sixth Conference on Machine Translation, pages 187–196, Online. Association for Computational Linguistics.