RAG has proven effective in enhancing the factual accuracy of LLMs by grounding their outputs in external, relevant information. However, most existing RAG implementations are limited to text-based corpora, which restricts their…
Multimodal Queries Require Multimodal RAG: Researchers from KAIST and DeepAuto.ai Propose UniversalRAG—A New Framework That Dynamically Routes Across Modalities and Granularities for Accurate and Efficient Retrieval-Augmented Generation
