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Updated: Jan 17, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Published on: December 6, 2024

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增强轨道碎片识别与Neo4j启用基于图形的检索增强生成多式大型语言模型的多式大型语言模型

Daniel S Roll1, Zeyneb Kurt2, Yulei Li1

  • 1Department of Mathematics, Physics and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University, Newcastle City Campus, College Street, Newcastle-upon-Tyne NE1 8ST, UK.

Sensors (Basel, Switzerland)
|September 19, 2025
PubMed
概括

一个新的基于图形的提取增强生成 (GraphRAG) 系统将Large Language and Vision Assistant (LLaVA) 与Neo4j图形数据库相结合. 这种方法通过检索结构化知识来提高轨道碎片检测中的AI准确性,减少AI幻觉.

关键词:
图形数据库 图形数据库获取知识 获取知识大型语言模型.轨道上的碎片提取增强生成的提取空间情境意识 空间情境意识

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