@inproceedings{oravecz-etal-2020-etranslations,
title = "e{T}ranslation{'}s Submissions to the {WMT} 2020 News Translation Task",
author = "Oravecz, Csaba and
Bontcheva, Katina and
Tihanyi, L{\'a}szl{\'o} and
Kolovratnik, David and
Bhaskar, Bhavani and
Lardilleux, Adrien and
Klocek, Szymon and
Eisele, Andreas",
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.26",
pages = "254--261",
abstract = "The paper describes the submissions of the eTranslation team to the WMT 2020 news translation shared task. Leveraging the experience from the team{'}s participation last year we developed systems for 5 language pairs with various strategies. Compared to last year, for some language pairs we dedicated a lot more resources to training, and tried to follow standard best practices to build competitive systems which can achieve good results in the rankings. By using deep and complex architectures we sacrificed direct re-usability of our systems in production environments but evaluation showed that this approach could result in better models that significantly outperform baseline architectures. We submitted two systems to the zero shot robustness task. These submissions are described briefly in this paper as well.",
}
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<abstract>The paper describes the submissions of the eTranslation team to the WMT 2020 news translation shared task. Leveraging the experience from the team’s participation last year we developed systems for 5 language pairs with various strategies. Compared to last year, for some language pairs we dedicated a lot more resources to training, and tried to follow standard best practices to build competitive systems which can achieve good results in the rankings. By using deep and complex architectures we sacrificed direct re-usability of our systems in production environments but evaluation showed that this approach could result in better models that significantly outperform baseline architectures. We submitted two systems to the zero shot robustness task. These submissions are described briefly in this paper as well.</abstract>
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%0 Conference Proceedings
%T eTranslation’s Submissions to the WMT 2020 News Translation Task
%A Oravecz, Csaba
%A Bontcheva, Katina
%A Tihanyi, László
%A Kolovratnik, David
%A Bhaskar, Bhavani
%A Lardilleux, Adrien
%A Klocek, Szymon
%A Eisele, Andreas
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F oravecz-etal-2020-etranslations
%X The paper describes the submissions of the eTranslation team to the WMT 2020 news translation shared task. Leveraging the experience from the team’s participation last year we developed systems for 5 language pairs with various strategies. Compared to last year, for some language pairs we dedicated a lot more resources to training, and tried to follow standard best practices to build competitive systems which can achieve good results in the rankings. By using deep and complex architectures we sacrificed direct re-usability of our systems in production environments but evaluation showed that this approach could result in better models that significantly outperform baseline architectures. We submitted two systems to the zero shot robustness task. These submissions are described briefly in this paper as well.
%U https://aclanthology.org/2020.wmt-1.26
%P 254-261
Markdown (Informal)
[eTranslation’s Submissions to the WMT 2020 News Translation Task](https://aclanthology.org/2020.wmt-1.26) (Oravecz et al., WMT 2020)
ACL
- Csaba Oravecz, Katina Bontcheva, László Tihanyi, David Kolovratnik, Bhavani Bhaskar, Adrien Lardilleux, Szymon Klocek, and Andreas Eisele. 2020. eTranslation’s Submissions to the WMT 2020 News Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 254–261, Online. Association for Computational Linguistics.