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From vectors to knowledge graphs: A comprehensive analysis of modern retrieval-augmented generation architectures

A study on modern retrieval-augmented generation architectures.

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From vectors to knowledge graphs: A comprehensive analysis of modern retrieval-augmented generation architectures

By Amir Abbas Kamalipour, Shahrokh Asadi, Mohammad Mahyar Amiri ChimehComputer Science Review
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The paper analyzes the evolution of retrieval-augmented generation (RAG) models from vector-based representations to knowledge graph-based ones. It provides a comprehensive overview of the current state-of-the-art in RAG architectures and their applications.

The authors discuss the benefits and limitations of using knowledge graphs in RAG models.

Abstract

The paper analyzes the evolution of retrieval-augmented generation (RAG) models from vector-based representations to knowledge graph-based ones. It provides a comprehensive overview of the current state-of-the-art in RAG architectures and their applications. The authors discuss the benefits and limitations of using knowledge graphs in RAG models.

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retrieval-augmented generationknowledge graphvector representationRAG architecturesKnowledge GraphsLarge Language ModelsRetrieval & RAGSemantic Interoperability
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