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RAG-KG-IL: A Multi-Agent Hybrid Framework for Reducing Hallucinations and Enhancing LLM Reasoning through RAG and Incremental Knowledge Graph Learning Integration
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RAG-KG-IL is a novel multi-agent hybrid framework that deeply integrates LLMs with KGs and an incremental learning approach. It aims to enhance LLM reasoning and reduce hallucinations, while LLM-agents actively generate, update, and reason over the Knowledge Graph, demonstrating mutual enhancement and combined reasoning capabilities. The explicit "KG Generation and Reasoning" component and evaluation of "Knowledge Creation and Causality Reasoning Capabilities" underscore its synergistic approach to reasoning.
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