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        <title>Tencent Neural Machine Translation Systems for the WMT20 News Translation Task</title>
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    <name type="personal">
        <namePart type="given">Shuangzhi</namePart>
        <namePart type="family">Wu</namePart>
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    <name type="personal">
        <namePart type="given">Xing</namePart>
        <namePart type="family">Wang</namePart>
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        <namePart type="given">Longyue</namePart>
        <namePart type="family">Wang</namePart>
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    <name type="personal">
        <namePart type="given">Fangxu</namePart>
        <namePart type="family">Liu</namePart>
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    <name type="personal">
        <namePart type="given">Jun</namePart>
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        <namePart type="given">Zhaopeng</namePart>
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        <dateIssued>2020-11</dateIssued>
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            <title>Proceedings of the Fifth Conference on Machine Translation</title>
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    <abstract>This paper describes Tencent Neural Machine Translation systems for the WMT 2020 news translation tasks. We participate in the shared news translation task on English łeftrightarrow Chinese and English \rightarrow German language pairs. Our systems are built on deep Transformer and several data augmentation methods. We propose a boosted in-domain finetuning method to improve single models. Ensemble is used to combine single models and we propose an iterative transductive ensemble method which can further improve the translation performance based on the ensemble results. We achieve a BLEU score of 36.8 and the highest chrF score of 0.648 on Chinese \rightarrow English task.</abstract>
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        <url>https://aclanthology.org/2020.wmt-1.34</url>
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        <date>2020-11</date>
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            <start>313</start>
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%0 Conference Proceedings
%T Tencent Neural Machine Translation Systems for the WMT20 News Translation Task
%A Wu, Shuangzhi
%A Wang, Xing
%A Wang, Longyue
%A Liu, Fangxu
%A Xie, Jun
%A Tu, Zhaopeng
%A Shi, Shuming
%A Li, Mu
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F wu-etal-2020-tencent
%X This paper describes Tencent Neural Machine Translation systems for the WMT 2020 news translation tasks. We participate in the shared news translation task on English łeftrightarrow Chinese and English \rightarrow German language pairs. Our systems are built on deep Transformer and several data augmentation methods. We propose a boosted in-domain finetuning method to improve single models. Ensemble is used to combine single models and we propose an iterative transductive ensemble method which can further improve the translation performance based on the ensemble results. We achieve a BLEU score of 36.8 and the highest chrF score of 0.648 on Chinese \rightarrow English task.
%U https://aclanthology.org/2020.wmt-1.34
%P 313-319

Markdown (Informal)

[Tencent Neural Machine Translation Systems for the WMT20 News Translation Task](https://aclanthology.org/2020.wmt-1.34) (Wu et al., WMT 2020)

• Tencent Neural Machine Translation Systems for the WMT20 News Translation Task (Wu et al., WMT 2020)

ACL

• Shuangzhi Wu, Xing Wang, Longyue Wang, Fangxu Liu, Jun Xie, Zhaopeng Tu, Shuming Shi, and Mu Li. 2020. Tencent Neural Machine Translation Systems for the WMT20 News Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 313–319, Online. Association for Computational Linguistics.