@InProceedings{pal-EtAl:2017:EACLshort,
  author    = {Pal, Santanu  and  Naskar, Sudip Kumar  and  Vela, Mihaela  and  Liu, Qun  and  van Genabith, Josef},
  title     = {Neural Automatic Post-Editing Using Prior Alignment and Reranking},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {349--355},
  abstract  = {We present a second-stage machine translation (MT) system based on a neural
	machine translation (NMT) approach to automatic post-editing (APE) that
	improves the translation quality provided by a first-stage MT system.
	Our APE system (APE\_Sym) is an extended version of an attention based NMT model
	with bilingual symmetry employing bidirectional models, mt--pe and pe--mt.
	APE translations produced by our system show statistically significant
	improvements over the first-stage MT, phrase-based APE and the best reported
	score on the WMT 2016 APE dataset by a previous neural APE system.
	Re-ranking (APE\_Rerank) of the n-best translations from the phrase-based APE
	and APE\_Sym systems provides further substantial improvements over the
	symmetric neural APE model.
	Human evaluation confirms that the APE\_Rerank generated PE translations improve
	on the previous best neural APE system at WMT 2016.},
  url       = {http://www.aclweb.org/anthology/E17-2056}
}