@InProceedings{aharoni-goldberg:2017:Short,
  author    = {Aharoni, Roee  and  Goldberg, Yoav},
  title     = {Towards String-To-Tree Neural Machine Translation},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {132--140},
  abstract  = {We present a simple method to incorporate syntactic information about the
	target language in a neural machine translation system by translating into
	linearized, lexicalized constituency trees. An experiment on the WMT16
	German-English news translation task resulted in an improved BLEU score when
	compared to a syntax-agnostic NMT baseline trained on the same dataset. An
	analysis of the translations from the syntax-aware system shows that it
	performs more reordering during translation in comparison to the baseline. A
	small-scale human evaluation also showed an advantage to the syntax-aware
	system.},
  url       = {http://aclweb.org/anthology/P17-2021}
}