2 papers
cs.IR2026
Teacher Retains Full Tokens, Student Merges Efficiently: TM20K for E-Commerce Sequence Modeling in Ad Recommendation
Xinchun Li, Duoru Zheng, Wenlin Zhao +13
Benefiting from ultra-long behavior sequence modeling, existing recommender systems bring users a better experience via simultaneously considering their long-term and short-term in…
cs.IR2026
TokenMixer-Large: Scaling Up Large Ranking Models in Industrial Recommenders
Yuchen Jiang, Jie Zhu, Xintian Han +18
While scaling laws for recommendation models have gained significant traction, existing architectures such as Wukong, HiFormer and DHEN, often struggle with sub-optimal designs and…