@inproceedings{chen-etal-2020-improving-efficiency,
    title = "Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction",
    author = "Chen, Mengyun  and
      Ge, Tao  and
      Zhang, Xingxing  and
      Wei, Furu  and
      Zhou, Ming",
    editor = "Webber, Bonnie  and
      Cohn, Trevor  and
      He, Yulan  and
      Liu, Yang",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.emnlp-main.581/",
    doi = "10.18653/v1/2020.emnlp-main.581",
    pages = "7162--7169",
    abstract = "We propose a novel language-independent approach to improve the efficiency for Grammatical Error Correction (GEC) by dividing the task into two subtasks: Erroneous Span Detection (ESD) and Erroneous Span Correction (ESC). ESD identifies grammatically incorrect text spans with an efficient sequence tagging model. Then, ESC leverages a seq2seq model to take the sentence with annotated erroneous spans as input and only outputs the corrected text for these spans. Experiments show our approach performs comparably to conventional seq2seq approaches in both English and Chinese GEC benchmarks with less than 50{\%} time cost for inference."
}