Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval. (arXiv:2201.05409v1 [cs.IR])

Ad-hoc search calls for the selection of appropriate answers from a
massive-scale corpus. Nowadays, the embedding-based retrieval (EBR) becomes a
promising solution, where deep learning based document representation and ANN
search techniques are allied to handle this task. However, a major challenge is
that the ANN index can be too large to fit into memory, given the considerable
size of answer corpus. In this work, we tackle this problem with Bi-Granular
Document Representation, where the lightweight sparse embeddings are indexed …

arxiv bi embedding