Large Language Models (LLMs) have revolutionized many areas of natural language processing, but they still face critical limitations when dealing with up-to-date facts, domain-specific information, or complex multi-hop reasoning. Retrieval-Augmented Generation (RAG) approaches aim to address these gaps by allowing language models to retrieve and integrate information from external sources. However, most existing graph-based RAG […]
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