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Book Open access Jul 2026

Graph Diffusion Gated Embeddings for Recommender Systems

Modern large-scale recommender systems rely on dense user and item embeddings, but using a full embedding table requires a large number of parameters. To reduce this cost, hashing tricks are commonly used to compress embedding tables. However, collisions and hard bucket assignments can degrade both performance and pers...

Seung-Chal Lee, Taeyoung Roh, Jiho Seo et al. · 0 citations

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