ChatLang-8: An LLM-Based Synthetic Data Generation Framework for Grammatical Error Correction
<|reference_start|>ChatLang-8: An LLM-Based Synthetic Data Generation Framework for Grammatical Error Correction: We explore and improve the capabilities of LLMs to generate data for grammatical error correction (GEC). When merely producing parallel sentences, their patterns are too simplistic to be valuable as a corpus. To address this issue, we propose an automated framework that includes a Subject Selector, Grammar Selector, Prompt Manager, and Evaluator. Additionally, we introduce a new dataset for GEC tasks, named ChatLang-8, which encompasses eight types of subject nouns and 23 types of grammar. It consists of 1 million pairs featuring human-like grammatical errors. Our experiments reveal that ChatLang-8 exhibits a more uniform pattern composition compared to existing GEC datasets. Furthermore, we observe improved model performance when using ChatLang-8 instead of existing GEC datasets. The experimental results suggest that our framework and ChatLang-8 are valuable resources for enhancing ChatGPT's data generation capabilities.<|reference_end|>
@article{park2024chatlang-8:,
    title={ChatLang-8: An LLM-Based Synthetic Data Generation Framework for
  Grammatical Error Correction},
    author={Jeiyoon Park, Chanjun Park, Heuiseok Lim},
    journal={arXiv preprint arXiv:2406.03202},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.03202},
    primaryClass={cs.CL cs.AI}
}