LawLuo: A Chinese Law Firm Co-run by LLM Agents

• URL: http://arxiv.org/abs/2407.16252v2
• Date: Sun, 4 Aug 2024 15:27:28 GMT
• Title: LawLuo: A Chinese Law Firm Co-run by LLM Agents
• Authors: Jingyun Sun, Chengxiao Dai, Zhongze Luo, Yangbo Chang, Yang Li,
• Abstract summary: Large Language Models (LLMs) deliver legal consultation services to users without a legal background. Existing Chinese legal LLMs limit interaction to a single model-user dialogue. We propose a novel legal dialogue framework that leverages the collaborative capabilities of multiple LLM agents, termed LawLuo.
• Score: 1.9857357818932064
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) demonstrate substantial potential in delivering legal consultation services to users without a legal background, attributed to their superior text comprehension and generation capabilities. Nonetheless, existing Chinese legal LLMs limit interaction to a single model-user dialogue, unlike the collaborative consultations typical of law firms, where multiple staff members contribute to a single consultation. This limitation prevents an authentic consultation experience. Additionally, extant Chinese legal LLMs suffer from critical limitations: (1) insufficient control over the quality of instruction fine-tuning data; (2) increased model hallucination resulting from users' ambiguous queries; and (3) a reduction in the model's ability to follow instructions over multiple dialogue turns. In response to these challenges, we propose a novel legal dialogue framework that leverages the collaborative capabilities of multiple LLM agents, termed LawLuo. This framework encompasses four agents: a receptionist, a lawyer, a secretary, and a boss, each responsible for different functionalities, collaboratively providing a comprehensive legal consultation to users. Additionally, we constructed two high-quality legal dialogue datasets, KINLED and MURLED, and fine-tuned ChatGLM-3-6b using these datasets. We propose a legal query clarification algorithm called ToLC. Experimental results demonstrate that LawLuo outperforms baseline LLMs, including GPT-4, across three dimensions: lawyer-like language style, the usefulness of legal advice, and the accuracy of legal knowledge. Our code and datasets are available at https://github.com/NEFUJing/LawLuo.

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