@InProceedings{ghader-monz:2017:I17-1,
  author    = {Ghader, Hamidreza  and  Monz, Christof},
  title     = {What does Attention in Neural Machine Translation Pay Attention to?},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {30--39},
  abstract  = {Attention in neural machine translation provides the possibility to encode
	relevant parts of the source sentence at each translation step. As a result,
	attention is considered to be an alignment model as well. However, there is no
	work that specifically studies attention and provides analysis of what is being
	learned by attention models. Thus, the question still remains that how
	attention is similar or different from the traditional alignment. In this
	paper, we provide detailed analysis of attention and compare it to traditional
	alignment. We answer the question of whether attention is only capable of
	modelling translational equivalent or it captures more information. We show
	that attention is different from alignment in some cases and is capturing
	useful information other than alignments.},
  url       = {http://www.aclweb.org/anthology/I17-1004}
}