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cs.IR2026
Rec-Distill: An Industrial Distillation Pipeline for Large-Scale Recommendation Models
Haoran Ding, Wenlin Zhao, Yuchen Jiang +16
Large recommendation models have demonstrated substantial potential gains under scaling laws, yet these gains are difficult to realize in industrial recommendation systems because…
cs.IR2024
Data Efficiency for Large Recommendation Models
Kshitij Jain, Jingru Xie, Kevin Regan +9
Large recommendation models (LRMs) are fundamental to the multi-billion dollar online advertising industry, processing massive datasets of hundreds of billions of examples before t…