@inproceedings{wang-etal-2018-tencent,
    title = "Tencent Neural Machine Translation Systems for {WMT}18",
    author = "Wang, Mingxuan  and
      Gong, Li  and
      Zhu, Wenhuan  and
      Xie, Jun  and
      Bian, Chao",
    editor = "Bojar, Ond{\v{r}}ej  and
      Chatterjee, Rajen  and
      Federmann, Christian  and
      Fishel, Mark  and
      Graham, Yvette  and
      Haddow, Barry  and
      Huck, Matthias  and
      Yepes, Antonio Jimeno  and
      Koehn, Philipp  and
      Monz, Christof  and
      Negri, Matteo  and
      N{\'e}v{\'e}ol, Aur{\'e}lie  and
      Neves, Mariana  and
      Post, Matt  and
      Specia, Lucia  and
      Turchi, Marco  and
      Verspoor, Karin",
    booktitle = "Proceedings of the Third Conference on Machine Translation: Shared Task Papers",
    month = oct,
    year = "2018",
    address = "Belgium, Brussels",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/W18-6429/",
    doi = "10.18653/v1/W18-6429",
    pages = "522--527",
    abstract = "We participated in the WMT 2018 shared news translation task on English{\ensuremath{\leftrightarrow}}Chinese language pair. Our systems are based on attentional sequence-to-sequence models with some form of recursion and self-attention. Some data augmentation methods are also introduced to improve the translation performance. The best translation result is obtained with ensemble and reranking techniques. Our Chinese{\textrightarrow}English system achieved the highest cased BLEU score among all 16 submitted systems, and our English{\textrightarrow}Chinese system ranked the third out of 18 submitted systems."
}