<ul><li>Researchers have proposed RAG-check, a comprehensive method to evaluate multi-modal RAG systems.</li><li>RAG-check consists of three components: relevancy evaluation, span categorization, and correctness assessment.</li><li>The evaluation results show performance variations across different RAG system configurations.</li><li>GPT-4o emerges as the most effective model for context generation in RAG systems.</li></ul>

RAG-Check: A Novel AI Framework for Hallucination Detection in Multi-Modal Retrieval-Augmented Generation Systems

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