@inproceedings{krubinski-etal-2020-samsung,
title = "{S}amsung {R}{\&}{D} Institute {P}oland submission to {WMT}20 News Translation Task",
author = "Krubi{\'n}ski, Mateusz and
Chochowski, Marcin and
Boczek, Bart{\l}omiej and
Koszowski, Miko{\l}aj and
Dobrowolski, Adam and
Szyma{\'n}ski, Marcin and
Przybysz, Pawe{\l}",
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-1.16",
pages = "181--190",
abstract = "This paper describes the submission to the WMT20 shared news translation task by Samsung R{\&}D Institute Poland. We submitted systems for six language directions: English to Czech, Czech to English, English to Polish, Polish to English, English to Inuktitut and Inuktitut to English. For each, we trained a single-direction model. However, directions including English, Polish and Czech were derived from a common multilingual base, which was later fine-tuned on each particular direction. For all the translation directions, we used a similar training regime, with iterative training corpora improvement through back-translation and model ensembling. For the En → Cs direction, we additionally leveraged document-level information by re-ranking the beam output with a separate model.",
}
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<abstract>This paper describes the submission to the WMT20 shared news translation task by Samsung R&D Institute Poland. We submitted systems for six language directions: English to Czech, Czech to English, English to Polish, Polish to English, English to Inuktitut and Inuktitut to English. For each, we trained a single-direction model. However, directions including English, Polish and Czech were derived from a common multilingual base, which was later fine-tuned on each particular direction. For all the translation directions, we used a similar training regime, with iterative training corpora improvement through back-translation and model ensembling. For the En → Cs direction, we additionally leveraged document-level information by re-ranking the beam output with a separate model.</abstract>
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%0 Conference Proceedings
%T Samsung R&D Institute Poland submission to WMT20 News Translation Task
%A Krubiński, Mateusz
%A Chochowski, Marcin
%A Boczek, Bartłomiej
%A Koszowski, Mikołaj
%A Dobrowolski, Adam
%A Szymański, Marcin
%A Przybysz, Paweł
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F krubinski-etal-2020-samsung
%X This paper describes the submission to the WMT20 shared news translation task by Samsung R&D Institute Poland. We submitted systems for six language directions: English to Czech, Czech to English, English to Polish, Polish to English, English to Inuktitut and Inuktitut to English. For each, we trained a single-direction model. However, directions including English, Polish and Czech were derived from a common multilingual base, which was later fine-tuned on each particular direction. For all the translation directions, we used a similar training regime, with iterative training corpora improvement through back-translation and model ensembling. For the En → Cs direction, we additionally leveraged document-level information by re-ranking the beam output with a separate model.
%U https://aclanthology.org/2020.wmt-1.16
%P 181-190
Markdown (Informal)
[Samsung R&D Institute Poland submission to WMT20 News Translation Task](https://aclanthology.org/2020.wmt-1.16) (Krubiński et al., WMT 2020)
ACL