2 papers
cs.IR2026
SMES: Towards Scalable Multi-Task Recommendation via Expert Sparsity
Yukun Zhang, Si Dong, Xu Wang +11
Industrial recommender systems typically rely on multi-task learning to estimate diverse user feedback signals and aggregate them for ranking. Recent advances in model scaling have…
cs.IR2024
HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou
Xu Wang, Jiangxia Cao, Zhiyi Fu +2
In this paper, we present the practical problems and the lessons learned at short-video services from Kuaishou. In industry, a widely-used multi-task framework is the Mixture-of-Ex…