@inproceedings{wu-wang-2020-cyut,
    title = "{CYUT} Team {C}hinese Grammatical Error Diagnosis System Report in {NLPTEA}-2020 {CGED} Shared Task",
    author = "Wu, Shih-Hung  and
      Wang, Junwei",
    editor = "YANG, Erhong  and
      XUN, Endong  and
      ZHANG, Baolin  and
      RAO, Gaoqi",
    booktitle = "Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications",
    month = dec,
    year = "2020",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.nlptea-1.12/",
    doi = "10.18653/v1/2020.nlptea-1.12",
    pages = "91--96",
    abstract = "This paper reports our Chinese Grammatical Error Diagnosis system in the NLPTEA-2020 CGED shared task. In 2020, we sent two runs with two approaches. The first one is a combination of conditional random fields (CRF) and a BERT model deep-learning approach. The second one is a BERT model deep-learning approach. The official results shows that our run1 achieved the highest precision rate 0.9875 with the lowest false positive rate 0.0163 on detection, while run2 gives a more balanced performance."
}