Chinese Spelling Correction: A Comprehensive Survey of Progress, Challenges, and Opportunities
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866916617836822528 |
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| author | Liu, Changchun Zhang, Kai Jiang, Junzhe Kong, Zixiao Liu, Qi Chen, Enhong |
| author_facet | Liu, Changchun Zhang, Kai Jiang, Junzhe Kong, Zixiao Liu, Qi Chen, Enhong |
| contents | Chinese Spelling Correction (CSC) is a critical task in natural language processing, aimed at detecting and correcting spelling errors in Chinese text. This survey provides a comprehensive overview of CSC, tracing its evolution from pre-trained language models to large language models, and critically analyzing their respective strengths and weaknesses in this domain. Moreover, we further present a detailed examination of existing benchmark datasets, highlighting their inherent challenges and limitations. Finally, we propose promising future research directions, particularly focusing on leveraging the potential of LLMs and their reasoning capabilities for improved CSC performance. To the best of our knowledge, this is the first comprehensive survey dedicated to the field of CSC. We believe this work will serve as a valuable resource for researchers, fostering a deeper understanding of the field and inspiring future advancements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_11508 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Chinese Spelling Correction: A Comprehensive Survey of Progress, Challenges, and Opportunities Liu, Changchun Zhang, Kai Jiang, Junzhe Kong, Zixiao Liu, Qi Chen, Enhong Computation and Language Artificial Intelligence Chinese Spelling Correction (CSC) is a critical task in natural language processing, aimed at detecting and correcting spelling errors in Chinese text. This survey provides a comprehensive overview of CSC, tracing its evolution from pre-trained language models to large language models, and critically analyzing their respective strengths and weaknesses in this domain. Moreover, we further present a detailed examination of existing benchmark datasets, highlighting their inherent challenges and limitations. Finally, we propose promising future research directions, particularly focusing on leveraging the potential of LLMs and their reasoning capabilities for improved CSC performance. To the best of our knowledge, this is the first comprehensive survey dedicated to the field of CSC. We believe this work will serve as a valuable resource for researchers, fostering a deeper understanding of the field and inspiring future advancements. |
| title | Chinese Spelling Correction: A Comprehensive Survey of Progress, Challenges, and Opportunities |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2502.11508 |