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cs.IR2026
LENS: A Staged Design for Interaction Granularity in Sequential CTR Prediction
Yuan Wang, Yue Liu, Jun Zhang +1
In sequential CTR prediction, a central design question is at what granularity the target should interact with the user behaviour sequence. Existing models mainly follow two routes…
cs.IR2026
Recurrent Preference Memory for Efficient Long-Sequence Generative Recommendation
Yixiao Chen, Yuan Wang, Yue Liu +9
Generative recommendation (GenRec) models typically model user behavior via full attention, but scaling to lifelong sequences is hindered by prohibitive computational costs and noi…
cs.LG2026
PRISM: Parallel Residual Iterative Sequence Model
Jie Jiang, Ke Cheng, Xin Xu +8
Generative sequence modeling faces a fundamental tension between the expressivity of Transformers and the efficiency of linear sequence models. Existing efficient architectures are…