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Abstract
The machine translation efficiency task challenges participants to make their systems faster and smaller with minimal impact on translation quality. How much quality to sacrifice for efficiency depends upon the application, so participants were encouraged to make multiple submissions covering the space of trade-offs. In total, there were 53 submissions by 4 teams. There were GPU, single-core CPU, and multi-core CPU hardware tracks as well as batched throughput or single-sentence latency conditions. Submissions showed hundreds of millions of words can be translated for a dollar, average latency is 5–17 ms, and models fit in 7.5–150 MB.- Anthology ID:
- 2021.wmt-1.68
- 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:
- 639–651
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.68/
- DOI:
- Bibkey:
- Cite (ACL):
- Kenneth Heafield, Qianqian Zhu, and Roman Grundkiewicz. 2021. Findings of the WMT 2021 Shared Task on Efficient Translation. In Proceedings of the Sixth Conference on Machine Translation, pages 639–651, Online. Association for Computational Linguistics.
- Cite (Informal):
- Findings of the WMT 2021 Shared Task on Efficient Translation (Heafield et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.68.pdf
- Software:
- 2021.wmt-1.68.Software.zip
Export citation
@inproceedings{heafield-etal-2021-findings,
title = "Findings of the {WMT} 2021 Shared Task on Efficient Translation",
author = "Heafield, Kenneth and
Zhu, Qianqian and
Grundkiewicz, Roman",
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-1.68/",
pages = "639--651",
abstract = "The machine translation efficiency task challenges participants to make their systems faster and smaller with minimal impact on translation quality. How much quality to sacrifice for efficiency depends upon the application, so participants were encouraged to make multiple submissions covering the space of trade-offs. In total, there were 53 submissions by 4 teams. There were GPU, single-core CPU, and multi-core CPU hardware tracks as well as batched throughput or single-sentence latency conditions. Submissions showed hundreds of millions of words can be translated for a dollar, average latency is 5{--}17 ms, and models fit in 7.5{--}150 MB."
}
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%0 Conference Proceedings %T Findings of the WMT 2021 Shared Task on Efficient Translation %A Heafield, Kenneth %A Zhu, Qianqian %A Grundkiewicz, Roman %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 heafield-etal-2021-findings %X The machine translation efficiency task challenges participants to make their systems faster and smaller with minimal impact on translation quality. How much quality to sacrifice for efficiency depends upon the application, so participants were encouraged to make multiple submissions covering the space of trade-offs. In total, there were 53 submissions by 4 teams. There were GPU, single-core CPU, and multi-core CPU hardware tracks as well as batched throughput or single-sentence latency conditions. Submissions showed hundreds of millions of words can be translated for a dollar, average latency is 5–17 ms, and models fit in 7.5–150 MB. %U https://aclanthology.org/2021.wmt-1.68/ %P 639-651
Markdown (Informal)
[Findings of the WMT 2021 Shared Task on Efficient Translation](https://aclanthology.org/2021.wmt-1.68/) (Heafield et al., WMT 2021)
- Findings of the WMT 2021 Shared Task on Efficient Translation (Heafield et al., WMT 2021)
ACL
- Kenneth Heafield, Qianqian Zhu, and Roman Grundkiewicz. 2021. Findings of the WMT 2021 Shared Task on Efficient Translation. In Proceedings of the Sixth Conference on Machine Translation, pages 639–651, Online. Association for Computational Linguistics.