首篇全面综述中文错字纠正进展与挑战的论文。
Chinese Spelling Correction: A Comprehensive Survey of Progress, Challenges, and Opportunities
- 梳理从预训练模型到大模型的CSC技术演进
- 分析现有数据集的局限性与核心挑战
- 展望大模型推理能力在纠错中的应用前景
中文错字纠正（CSC）是自然语言处理中的关键任务，旨在检测并修正中文文本中的拼写错误。本文首次系统综述了该领域的研究进展，回顾了从预训练语言模型到大语言模型（LLM）的技术演进，并深入分析了各类模型在该任务中的优劣。同时，本文详细评估了现有基准数据集，指出了其内在挑战与局限性。最后，提出了未来的研究方向，特别强调利用大模型的推理能力以提升纠错性能。本文为该领域提供了首个全面的综述，期望成为研究人员的重要参考，推动该方向的持续发展。
原文摘要 · Abstract (English)
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.
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