UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities

In three linesUniversalRAG extends retrieval-augmented generation (RAG) to heterogeneous multi-modal corpora (text, images, videos) with variable granularities. The framework proposes modality-aware routing to avoid intra-modal bias and dynamically retrieve from the appropriate corpus. Validated on 10 multi-modal benchmarks.

Summary generated by Claude — human-verified