@inproceedings{wang-etal-2020-chinese,
title = "{C}hinese Grammatical Correction Using {BERT}-based Pre-trained Model",
author = "Wang, Hongfei and
Kurosawa, Michiki and
Katsumata, Satoru and
Komachi, Mamoru",
editor = "Wong, Kam-Fai and
Knight, Kevin and
Wu, Hua",
booktitle = "Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing",
month = dec,
year = "2020",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.aacl-main.20",
doi = "10.18653/v1/2020.aacl-main.20",
pages = "163--168",
abstract = "In recent years, pre-trained models have been extensively studied, and several downstream tasks have benefited from their utilization. In this study, we verify the effectiveness of two methods that incorporate a pre-trained model into an encoder-decoder model on Chinese grammatical error correction tasks. We also analyze the error type and conclude that sentence-level errors are yet to be addressed.",
}
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%0 Conference Proceedings
%T Chinese Grammatical Correction Using BERT-based Pre-trained Model
%A Wang, Hongfei
%A Kurosawa, Michiki
%A Katsumata, Satoru
%A Komachi, Mamoru
%Y Wong, Kam-Fai
%Y Knight, Kevin
%Y Wu, Hua
%S Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing
%D 2020
%8 December
%I Association for Computational Linguistics
%C Suzhou, China
%F wang-etal-2020-chinese
%X In recent years, pre-trained models have been extensively studied, and several downstream tasks have benefited from their utilization. In this study, we verify the effectiveness of two methods that incorporate a pre-trained model into an encoder-decoder model on Chinese grammatical error correction tasks. We also analyze the error type and conclude that sentence-level errors are yet to be addressed.
%R 10.18653/v1/2020.aacl-main.20
%U https://aclanthology.org/2020.aacl-main.20
%U https://doi.org/10.18653/v1/2020.aacl-main.20
%P 163-168
Markdown (Informal)
[Chinese Grammatical Correction Using BERT-based Pre-trained Model](https://aclanthology.org/2020.aacl-main.20) (Wang et al., AACL 2020)
ACL
- Hongfei Wang, Michiki Kurosawa, Satoru Katsumata, and Mamoru Komachi. 2020. Chinese Grammatical Correction Using BERT-based Pre-trained Model. In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pages 163–168, Suzhou, China. Association for Computational Linguistics.