@inproceedings{sorokin-2022-improved,
    title = "Improved grammatical error correction by ranking elementary edits",
    author = "Sorokin, Alexey",
    editor = "Goldberg, Yoav  and
      Kozareva, Zornitsa  and
      Zhang, Yue",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.emnlp-main.785/",
    doi = "10.18653/v1/2022.emnlp-main.785",
    pages = "11416--11429",
    abstract = "We offer a two-stage reranking method for grammatical error correction: the first model serves as edit generator, while the second classifies the proposed edits as correct or false. We show how to use both encoder-decoder and sequence labeling models for the first step of our pipeline. We achieve state-of-the-art quality on BEA 2019 English dataset even using weak BERT-GEC edit generator. Combining our roberta-base scorer with state-of-the-art GECToR edit generator, we surpass GECToR by 2-3{\%}. With a larger model we establish a new SOTA on BEA development and test sets. Our model also sets a new SOTA on Russian, despite using smaller models and less data than the previous approaches."
}