Multi Vector Retrieval

Multi-vector retrieval (MVR) enhances information retrieval by representing documents and queries as collections of vectors, enabling more nuanced comparisons than single-vector approaches. Current research focuses on improving efficiency and scalability of MVR, particularly by reducing the substantial storage requirements associated with token-level representations, through techniques like token pooling and optimized indexing strategies. These advancements are significant because they address key limitations hindering the widespread adoption of MVR in large-scale applications, such as question answering and large language model-based systems, improving both speed and accuracy.