Tao Yang

Recent work on neural sparse retrieval has demonstrated strong relevance by leveraging Large Language Models (LLMs) for semantic term expansion. However, learned models paired with previous sparsification techniques still yield overly long document and query vectors partly due to a large LLM voca...

Learned sparse retrieval (LSR) is a popular method for first-stage retrieval because it combines the semantic matching of language models with efficient CPU-friendly algorithms. Previous work aggregates blocks into ''superblocks'' to quickly skip the visitation of blocks during query processing b...

Document clustering is a common technique used in sparse retrieval to group similar documents together. The K-means method has been widely adopted to group similar sparse vectors together, but it is not scalable when dealing with a large number of clusters, and the bipartite graph partitioning (B...