collaborators

5 papers

cs.IR2026

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…

cs.IR2026

Bumblebee: Interleaved Mixed-Layer Building Blocks for Large-Scale Recommendation Systems

David Bauer, Cancan Zhang, Wenshun Liu +11

Recommendation systems have undergone significant transformations in the past years. The transition from traditional feature interaction modules to generative next-action predictio…

cs.LG2025

Target-Aware Early Stage Ranking

Juhee Hong, Meng Liu, Shengzhi Wang +18

Early Stage Ranking (ESR) in large-scale recommendation systems is dominated by ''user--item decoupling'' Two Tower architectures, which scale efficiently but cannot capture fine-g…

cs.IR2025

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…

cs.IR2025

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…