metadata
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.
Links
- Paper: CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards
- GitHub Repository: 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:
@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},
}