1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.IR2026
UNIQUE: A Unified Retrieval and Ranking System for Large-Scale Feed Recommendation
Zhuang Liu, Yongkang Fu, Zuodong Yang +6
Industrial mobile feed systems rely on a retrieval-ranking pipeline to serve large-scale, heterogeneous, and fast-changing content under strict latency constraints. However, existi…
cs.IR2026
MuSeR: Scalable Long-sequence Recommendation with Multi-interest Modeling
Yongkang Fu, Beining Bao, Yu Jiang +10
Ultra-long user behavior sequences carry rich signals of stable and diverse preferences, yet industrial recommender systems typically truncate histories to a few hundred actions un…
cs.IR2021★ 1 cited
JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu
Hao Liu, Qian Gao, Jiang Li +9
In modern internet industries, deep learning based recommender systems have became an indispensable building block for a wide spectrum of applications, such as search engine, news…