AI RESEARCH
MUSS: Multilevel Subset Selection for Relevance and Diversity
arXiv CS.LG
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ArXi:2503.11126v3 Announce Type: replace The problem of relevant and diverse subset selection has a wide range of applications, including recommender systems and retrieval-augmented generation (RAG). For example, in recommender systems, one is interested in selecting relevant items, while providing a diversified recommendation. Constrained subset selection problem is NP-hard, and popular approaches such as Maximum Marginal Relevance (MMR) are based on greedy selection. Many real-world applications involve large data, but the original MMR work did not consider distributed selection.