构建合规的日本医疗诉讼RAG系统，确保法律与时间准确性
RAG System for Supporting Japanese Litigation Procedures: Faithful Response Generation Complying with Legal Norms
- 基于RAG框架设计，严格遵循禁止使用私人知识原则
- 生成回答完全源自检索内容，保持上下文忠实性
- 检索结果附带对应争议点的时间戳，符合法律时效要求
本研究探讨了基于检索增强生成（RAG）的大型语言模型系统在支持日本医疗诉讼程序时所需具备的关键组件，以确保符合法律规范。在诉讼中，专家委员（如医生、建筑师、会计师、工程师）提供专业知识帮助法官厘清争议点。若用RAG-based LLM替代此类专家角色，则必须严格遵守法律规范。具体提出三项要求：(1) 检索模块需依据禁止使用私人知识的原则，获取与争议问题相关的外部知识；(2) 生成的回答必须源于RAG提供的上下文，且忠实于该上下文；(3) 检索模块必须引用与争议点对应的适当时间戳外部知识。本文讨论满足这些要求的RAG系统设计。
原文摘要 · Abstract (English)
This study discusses the essential components that a Retrieval-Augmented Generation (RAG)-based LLM system should possess in order to support Japanese medical litigation procedures complying with legal norms. In litigation, expert commissioners, such as physicians, architects, accountants, and engineers, provide specialized knowledge to help judges clarify points of dispute. When considering the substitution of these expert roles with a RAG-based LLM system, the constraint of strict adherence to legal norms is imposed. Specifically, three requirements arise: (1) the retrieval module must retrieve appropriate external knowledge relevant to the disputed issues in accordance with the principle prohibiting the use of private knowledge, (2) the responses generated must originate from the context provided by the RAG and remain faithful to that context, and (3) the retrieval module must reference external knowledge with appropriate timestamps corresponding to the issues at hand. This paper discusses the design of a RAG-based LLM system that satisfies these requirements.
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