MUVERA: Efficient Multi-Vector Retrieval

Modern information retrieval relies on neural embedding models, but while multi-vector models offer higher accuracy, their computational complexity leads to inefficiency. Researchers introduce MUVERA, a novel algorithm that transforms complex multi-vector retrieval into simpler single-vector maximum inner product search (MIPS) by constructing fixed dimensional encodings (FDEs). This significantly improves efficiency without sacrificing accuracy. The open-source implementation is available on GitHub.