SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG

Researchers have developed SmartChunk retrieval, a query-adaptive framework that improves retrieval-augmented generation (RAG) systems by dynamically adjusting chunk sizes and compression for document question answering. The system uses a planner to predict optimal chunk abstraction levels and a compression module to create efficient embeddings, outperforming existing RAG baselines while reducing costs.