Matthias Petri

Accelerating Learned Sparse Indexes Via Term Impact Decomposition

Novel inverted index-based learned sparse ranking models provide more effective, but less efficient, retrieval performance compared to traditional ranking models like BM25. In this paper, we introduce a technique we call postings clipping to improve the query efficiency of learned representations. O…