Survey of Chinese Grammatical Error Correction: Datasets, Methods, and Future Directions
Researchers have published a comprehensive survey of Chinese Grammatical Error Correction (CGEC), covering datasets, annotation schemes, evaluation methods, and system development from rule-based to large language model approaches. CGEC serves both second-language learners and native Chinese speakers in academic and professional writing contexts, presenting unique technical challenges distinct from English grammatical error correction. The survey identifies key open problems—including inconsistent annotation standards and word segmentation ambiguity—and outlines future directions for the field.
The survey, posted to arXiv's Computation and Language section, provides a structured review of the CGEC research landscape, tracing the field's evolution from early rule-based and statistical systems through neural architectures to modern Transformer-based and large pre-trained language models. The authors examine existing CGEC datasets, noting limitations in their scope and a lack of standardization that complicates cross-study comparisons. A significant portion of the work addresses annotation challenges specific to Chinese, particularly word segmentation ambiguity and the classification of error types that do not map cleanly onto frameworks developed for English. Evaluation metrics are also analyzed, with attention to how English GEC benchmarks have been adapted for Chinese, including character-level scoring and multi-reference evaluation. The survey concludes by identifying future priorities such as refining annotation standards, addressing segmentation-related challenges, and exploring multilingual approaches to improve CGEC system performance.
What's missing
The survey is a preprint and has not yet undergone formal peer review. It does not report empirical results of its own, so claims about the relative performance of different CGEC system generations rest on the authors' synthesis of prior literature, which may reflect selection bias in which studies were included.
What different sources said
- arXiv cs.CLCenter
Chinese Grammatical Error Correction: A Survey
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