@InProceedings{hitomi-EtAl:2017:I17-2,
  author    = {Hitomi, Yuta  and  Tamori, Hideaki  and  Okazaki, Naoaki  and  Inui, Kentaro},
  title     = {Proofread Sentence Generation as Multi-Task Learning with Editing Operation Prediction},
  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     = {436--441},
  abstract  = {This paper explores the idea of robot editors, automated proofreaders that
	enable journalists to improve the quality of their articles.
	We propose a novel neural model of multi-task learning that both generates
	proofread sentences and predicts the editing operations required to rewrite the
	source sentences and create the proofread ones.
	The model is trained using logs of the revisions made professional editors
	revising draft newspaper articles written by journalists.
	Experiments demonstrate the effectiveness of our multi-task learning approach
	and the potential value of using revision logs for this task.},
  url       = {http://www.aclweb.org/anthology/I17-2074}
}