Summary of Lawluo: a Multi-agent Collaborative Framework For Multi-round Chinese Legal Consultation, by Jingyun Sun et al.
LawLuo: A Multi-Agent Collaborative Framework for Multi-Round Chinese Legal Consultation
by Jingyun Sun, Chengxiao Dai, Zhongze Luo, Yangbo Chang, Yang Li
First submitted to arxiv on: 23 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)
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| 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 research proposes a novel multi-agent framework called LawLuo for Chinese legal consultations, which simulates real-world collaborations between multiple professionals to provide tailored responses. The framework includes four agents: receptionist, lawyer, secretary, and boss, each with distinct roles in assessing user intent, interacting with users, organizing conversation records, and evaluating performance. To train these agents, the authors developed fine-tuning datasets that follow different legal instructions. Additionally, they introduced a case graph-based RAG to help the lawyer agent address vague user inputs. Experimental results demonstrate LawLuo’s effectiveness in generating personalized and professional responses, handling ambiguous queries, and following legal instructions in multi-turn conversations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary LawLuo is a new way for computers to give advice on the law. Right now, most computer programs that offer legal help are like a single lawyer who answers questions one by one. But real-life lawyers often work together to provide better advice. The LawLuo system tries to mimic this teamwork by using multiple “agents” (or computer programs) that work together to give more personalized and helpful responses. |
Keywords
» Artificial intelligence » Fine tuning » Rag
