Exploring New Frontiers of Deep Learning in Legal Practice: A Case Study of Large Language Models

Yixu Wang; Wenpin Qian; Hong Zhou; Jianfeng Chen; Kai Tan

doi:10.62051/ijcsit.v1n1.18

Authors

Yixu Wang
Wenpin Qian
Hong Zhou
Jianfeng Chen
Kai Tan

DOI:

https://doi.org/10.62051/ijcsit.v1n1.18

Keywords:

Large language model, ChatLaw, Legal text, Deep learning

Abstract

The LLM wave brought by ChatGPT has swept various vertical fields. Medical, finance, finance and other fields have gradually had their own exclusive large models, such as BloombergGPT, herbal medicine, Huatu, ChatMed, etc. In the legal field, we have seen LawGPT and Lawyers-LLAMA two preliminary open source models. People often think that by using domain-specific knowledge to fine-tune the model, you can get satisfactory results, but the legal field, because of its inherent requirements for accuracy, simply fine-tuning with some legal dialogue data is not enough to support the needs of real legal scenarios. Therefore, the large language model is obviously the most active field of AI at present, open source/closed source models continue to emerge, new research papers emerge in an endless stream, but as practitioners, how to truly understand the capabilities and limitations of the large language model, how to apply the large language model? The present has long been worth thinking deeply. In this paper, we propose a large language model for open source law called ChatLaw.

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