Thibault Formal

SPARSEUP: Towards Better Recipes for Training Modern Learned Sparse Retrievers

Learned sparse embeddings are a powerful alternative to dense retrieval, yet they have fallen behind single-vector and late interaction models. One reason for their limited adoption is that they are notoriously difficult to train, generally requiring very tight conditions to converge. We present a recipe for training S...