3 papers
cs.LG2026
MBD: A Model-Based Debiasing Framework Across User, Content, and Model Dimensions
Yuantong Li, Lei Yuan, Zhihao Zheng +27
Modern recommendation systems rank candidates by aggregating multiple behavioral signals through a value model. However, many commonly used signals are inherently affected by heter…
cs.IR2026
GEMs: Breaking the Long-Sequence Barrier in Generative Recommendation with a Multi-Stream Decoder
Yu Zhou, Chengcheng Guo, Kuo Cai +6
While generative recommendations (GR) possess strong sequential reasoning capabilities, they face significant challenges when processing extremely long user behavior sequences: the…
cs.IR2026
Coarse-to-Fine Long-term Interest Modeling for Generative Recommendation
Shiteng Cao, Junda She, Ji Liu +9
Leveraging long-term user behavioral patterns is a key trajectory for enhancing the accuracy of modern recommender systems. While generative recommender systems have emerged as a t…