Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets

Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli +2

Learned sparse text embeddings have gained popularity due to their effectiveness in top-k retrieval and inherent interpretability. Their distributional idiosyncrasies, however, hav…