@InProceedings{sakaguchi-post-vandurme:2017:I17-2,
  author    = {Sakaguchi, Keisuke  and  Post, Matt  and  Van Durme, Benjamin},
  title     = {Grammatical Error Correction with Neural Reinforcement Learning},
  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     = {366--372},
  abstract  = {We propose a neural encoder-decoder model with reinforcement learning (NRL) for
	grammatical error correction (GEC). Unlike conventional maximum likelihood
	estimation (MLE), the model directly optimizes towards an objective that
	considers a sentence-level, task-specific evaluation metric, avoiding the
	exposure bias issue in MLE. We demonstrate that NRL outperforms MLE both in
	human and automated evaluation metrics, achieving the state-of- the-art on a
	fluency-oriented GEC corpus.},
  url       = {http://www.aclweb.org/anthology/I17-2062}
}