Summary of Lawgpt: a Chinese Legal Knowledge-enhanced Large Language Model, by Zhi Zhou et al.
LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model
by Zhi Zhou, Jiang-Xin Shi, Peng-Xiao Song, Xiao-Wen Yang, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li
First submitted to arxiv on: 7 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the limitations of large language models (LLMs) in handling practical Chinese legal tasks. While LLMs show remarkable capabilities in various downstream tasks, they struggle to meet actual requirements due to data privacy concerns with proprietary models and lack of legal knowledge with open-source models. To overcome these issues, the authors introduce LawGPT, an open-source model designed specifically for Chinese legal applications. LawGPT consists of two key components: legal-oriented pre-training and legal supervised fine-tuning. The model is trained on large-scale Chinese legal documents to incorporate legal domain knowledge and further improved through a knowledge-driven instruction dataset. Experimental results demonstrate that LawGPT outperforms the open-source LLaMA 7B model. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models can do many things, but they’re not great at helping with practical legal tasks in China. The problem is that these models don’t always follow important rules to keep sensitive information private, and even when they do, they often don’t know enough about the law to help very much. To solve this problem, researchers created a new model called LawGPT. This model is special because it was designed just for Chinese legal tasks and can work well in those areas where other models struggle. |
Keywords
» Artificial intelligence » Fine tuning » Llama » Supervised
