PolyRAG: A Multi-Agent Multimodal Retrieval-Augmented Generation System for Heterogeneous Document Intelligence
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by reducing hallucinations and improving factual accuracy. Most RAG implementations, however, are restricted to a single data modality. Real-world document collections span PDFs, spreadsheets, audio, video and images simultaneously. This paper i...