| license: mit | |
| task_categories: | |
| - text-generation | |
| language: | |
| - zh | |
| tags: | |
| - text-correction | |
| - cgec | |
| - chain-of-thought | |
| # CSRP: Chain-of-Thought Reasoning for Chinese Text Correction | |
| This dataset contains the 340,000 Chain-of-Thought (CoT) reasoning samples introduced in the paper [CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards](https://huggingface.co/papers/2606.00020). | |
| ## Links | |
| - **Paper**: [CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards](https://huggingface.co/papers/2606.00020) | |
| - **GitHub Repository**: [TW-NLP/ChineseErrorCorrector](https://github.com/TW-NLP/ChineseErrorCorrector) | |
| ## Dataset Summary | |
| The CSRP dataset is designed to enhance Chinese Grammatical Error Correction (CGEC) by providing explicit error reasoning (Chain-of-Thought) for corrections. This diagnostic transparency helps models internalize linguistic priors and effectively mitigates over-correction bias. | |
| The dataset includes 340,000 balanced samples covering various error types: | |
| - Spelling errors (错别字) | |
| - Word collocation errors (词语搭配错误) | |
| - Word order errors (语序错误) | |
| - Component omission or redundancy (成分残缺/赘余) | |
| - Semantic logic issues (语义逻辑不通) | |
| ## Citation | |
| If you use this dataset, please cite: | |
| ```bibtex | |
| @misc{tian2026csrpchainofthoughtreasoningchinese, | |
| title={CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards}, | |
| author={Wei Tian and Yuhao Zhou and Man Lan}, | |
| year={2026}, | |
| eprint={2606.00020}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| url={https://arxiv.org/abs/2606.00020}, | |
| } | |
| ``` |