3 papers
cs.LG2026
Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation
Guoming Li, Shangyu Zhang, Junwei Pan +7
Scaling recommendation models is a central challenge in recommender systems. Recently, RankMixer has emerged as an effective solution, operating on a unified token representation a…
cs.IR2024
Efficient Transfer Learning Framework for Cross-Domain Click-Through Rate Prediction
Qi Liu, Xingyuan Tang, Jianqiang Huang +9
Natural content and advertisement coexist in industrial recommendation systems but differ in data distribution. Concretely, traffic related to the advertisement is considerably spa…
cs.IR2024
Dual Test-time Training for Out-of-distribution Recommender System
Xihong Yang, Yiqi Wang, Jin Chen +5
Deep learning has been widely applied in recommender systems, which has achieved revolutionary progress recently. However, most existing learning-based methods assume that the user…