4 papers · 1 filter
Inherit4Rec: Parameter Inheritance for Efficient Scaling of Recommendation Models
Ruihao Zhang, Bo Chen, Xiao Wang +8
Scaling model capacity has emerged as an effective approach to overcoming performance bottlenecks in industrial recommender systems. However, repeatedly training new models from sc…
UniFormer: Efficient and Unified Model-Centric Scaling for Industrial Recommendation
Bo Chen, Jinlong Jiao, Tijian Hu +12
Recently, substantial progress has been made in industrial recommendation through component-centric model scaling, where individual components such as behavior modeling, feature in…
OneReason Technical Report
OneRec Team, Biao Yang, Boyang Ding +81
Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, advertising, and e-commerce. Howev…
DIET: Learning to Distill Dataset Continually for Recommender Systems
Jiaqing Zhang, Hao Wang, Mingjia Yin +6
Modern deep recommender models are trained under a continual learning paradigm, relying on massive and continuously growing streaming behavioral logs. In large-scale platforms, ret…