@InProceedings{liao-EtAl:2017:I17-4,
  author    = {Liao, Quanlei  and  Wang, Jin  and  Yang, Jinnan  and  Zhang, Xuejie},
  title     = {YNU-HPCC at IJCNLP-2017 Task 1: Chinese Grammatical Error Diagnosis Using a Bi-directional LSTM-CRF Model},
  booktitle = {Proceedings of the IJCNLP 2017, Shared Tasks},
  month     = {December},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {73--77},
  abstract  = {Building a system to detect Chinese grammatical errors is a challenge for
	natural-language processing researchers. As Chinese learners are increasing,
	developing such a system can help them study Chinese more easily. This paper
	introduces a bi-directional long short-term memory (BiLSTM) - conditional
	random field (CRF) model to produce the sequences that indicate an error type
	for every position of a sentence, since we regard Chinese grammatical error
	diagnosis (CGED) as a sequence-labeling problem.},
  url       = {http://www.aclweb.org/anthology/I17-4011}
}