@InProceedings{khayrallah-EtAl:2017:I17-2,
  author    = {Khayrallah, Huda  and  Kumar, Gaurav  and  Duh, Kevin  and  Post, Matt  and  Koehn, Philipp},
  title     = {Neural Lattice Search for Domain Adaptation in Machine Translation},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {20--25},
  abstract  = {Domain adaptation is a major challenge for neural machine translation (NMT).
	Given unknown words or new domains, NMT systems tend to generate fluent
	translations at the expense of adequacy. We present a stack-based lattice
	search algorithm for NMT and show that constraining its search space with
	lattices generated by phrase-based machine translation (PBMT) improves
	robustness. We report consistent BLEU score gains across four diverse domain
	adaptation tasks involving medical, IT, Koran, or subtitles texts.},
  url       = {http://www.aclweb.org/anthology/I17-2004}
}