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most citedbeeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems

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cs.IR2025

The Future is Sparse: Embedding Compression for Scalable Retrieval in Recommender Systems

Petr Kasalický, Martin Spišák, Vojtěch Vančura +3

Industry-scale recommender systems face a core challenge: representing entities with high cardinality, such as users or items, using dense embeddings that must be accessible during…