2 papers
cs.IR2026
SlimPer: Make Personalization Model Slim and Smart
Siqi Wang, Xianjie Chen, Shaofeng Deng +42
Transformer-style architectures are increasingly adopted for industrial recommendation systems, yet they inherit a design premise misaligned with the task: generative models rely o…
cs.IR2026
Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale
Liang Guo, Ge Song, Litao Deng +9
Modern Deep Learning Recommendation Models (DLRMs) follow scaling laws with sequence length, driving the frontier toward ultra-long User Interaction History (UIH). However, the ind…