GLIE aims to cut vector storage for visual document search, a preprint announcement says

A post introducing GLIE—Generative Late-Interaction Embeddings for Visual Document Retrieval—describes a two-stage search process. A handful of stored vectors, numerical representations of each page, serve as the search index. According to the announcement, a small shared decoder then regenerates the full vector set only for the top candidates so they can be reranked.