Chinese Grammatical Correction Using BERT-based Pre-trained Model
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Abstract (arXiv)
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 BERT-based pre-trained model developed by Cui et al. (2020) 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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Nov 2020.
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Citing papers per year: 2021: 2; 2022: 3; 2023: 0; 2024: 0; 2025: 1.
6 papers.
- 2021Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correctioncited by 19
- 2022A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Modelcited by 16
- 2022uChecker: Masked Pretrained Language Models as Unsupervised Chinese Spelling Checkerscited by 9
- 2021An Alignment-Agnostic Model for Chinese Text Error Correctioncited by 1
- 2022Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errorscited by 1
- 2025Tgea: An error-annotated dataset and benchmark tasks for text generation from pretrained language modelscited by 1
- 2025Tgea: An error-annotated dataset and benchmark tasks for text generation from pretrained language models6 Mar 2025
- 2022uChecker: Masked Pretrained Language Models as Unsupervised Chinese Spelling Checkers15 Sep 2022
- 2022Pretraining Chinese BERT for Detecting Word Insertion and Deletion Errors26 Apr 2022
- 2022A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model26 Jan 2022
- 2021Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction3 Jun 2021
- 2021An Alignment-Agnostic Model for Chinese Text Error Correction15 Apr 2021