4 papers
WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture
Renqin Cai, Dawei Sun, Yuanjun Yao +8
As scalability becomes increasingly important in recommendation modeling, recent architectures have advanced the modeling of two broad sources of ranking signals along separate pat…
Bending the Scaling Law Curve in Large-Scale Recommendation Systems
Qin Ding, Kevin Course, Linjian Ma +19
Learning from user interaction history through sequential models has become a cornerstone of large-scale recommender systems. Recent advances in large language models have revealed…
Request-Only Optimization for Recommendation Systems
Liang Guo, Wei Li, Lucy Liao +25
Deep Learning Recommendation Models (DLRMs) represent one of the largest machine learning applications on the planet. Industry-scale DLRMs are trained with petabytes of recommendat…
Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
Dai Li, Kevin Course, Wei Li +13
Scaling laws have been established for recommender systems, yet efficiently deploying foundation model (FM) across multiple recommendation surfaces remains a major unsolved challen…