@InProceedings{li-EtAl:2016:WAT2016,
  author    = {Li, Shaotong  and  Xu, JinAn  and  Chen, Yufeng  and  Zhang, Yujie},
  title     = {System Description of bjtu\_nlp Neural Machine Translation System},
  booktitle = {Proceedings of the 3rd Workshop on Asian Translation (WAT2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {104--110},
  abstract  = {This paper presents our machine translation system that developed for the
	WAT2016 evalua-tion tasks of ja-en, ja-zh, en-ja, zh-ja, JPCja-en, JPCja-zh,
	JPCen-ja, JPCzh-ja. We build our system based on encoder--decoder framework by
	integrating recurrent neural network (RNN) and gate recurrent unit (GRU), and
	we also adopt an attention mechanism for solving the problem of information
	loss. Additionally, we propose a simple translation-specific approach to
	resolve the unknown word translation problem. Experimental results show that
	our system performs better than the baseline statistical machine translation
	(SMT) systems in each task. Moreover, it shows that our proposed approach of
	unknown word translation performs effec-tively improvement of translation
	results.},
  url       = {http://aclweb.org/anthology/W16-4608}
}