@InProceedings{niu-rao-carpuat:2018:C18-1,
  author    = {Niu, Xing  and  Rao, Sudha  and  Carpuat, Marine},
  title     = {Multi-Task Neural Models for Translating Between Styles Within and Across Languages},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1008--1021},
  abstract  = {Generating natural language requires conveying content in an appropriate style. We explore two related tasks on generating text of varying formality: monolingual formality transfer and formality-sensitive machine translation. We propose to solve these tasks jointly using multi-task learning, and show that our models achieve state-of-the-art performance for formality transfer and are able to perform formality-sensitive translation without being explicitly trained on style-annotated translation examples.},
  url       = {http://www.aclweb.org/anthology/C18-1086}
}