LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

التفاصيل البيبلوغرافية
العنوان: LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model
المؤلفون: Zhou, Zhi, Shi, Jiang-Xin, Song, Peng-Xiao, Yang, Xiao-Wen, Jin, Yi-Xuan, Guo, Lan-Zhe, Li, Yu-Feng
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
الوصف: Large language models (LLMs), including both proprietary and open-source models, have showcased remarkable capabilities in addressing a wide range of downstream tasks. Nonetheless, when it comes to practical Chinese legal tasks, these models fail to meet the actual requirements. Proprietary models do not ensure data privacy for sensitive legal cases, while open-source models demonstrate unsatisfactory performance due to their lack of legal knowledge. To address this problem, we introduce LawGPT, the first open-source model specifically designed for Chinese legal applications. LawGPT comprises two key components: legal-oriented pre-training and legal supervised fine-tuning. Specifically, we employ large-scale Chinese legal documents for legal-oriented pre-training to incorporate legal domain knowledge. To further improve the model's performance on downstream legal tasks, we create a knowledge-driven instruction dataset for legal supervised fine-tuning. Our experimental results demonstrate that LawGPT outperforms the open-source LLaMA 7B model. Our code and resources are publicly available at https://github.com/pengxiao-song/LaWGPT and have received 5.7K stars on GitHub.
Comment: Technical Report
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2406.04614
رقم الأكسشن: edsarx.2406.04614
قاعدة البيانات: arXiv