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cs.AI2026
CollectiveKV: Decoupling and Sharing Collaborative Information in Sequential Recommendation
Jingyu Li, Zhaocheng Du, Qianhui Zhu +5
Sequential recommendation models are widely used in applications, yet they face stringent latency requirements. Mainstream models leverage the Transformer attention mechanism to im…
cs.AI2026
Length-Adaptive Interest Network for Balancing Long and Short Sequence Modeling in CTR Prediction
Zhicheng Zhang, Zhaocheng Du, Jieming Zhu +8
User behavior sequences in modern recommendation systems exhibit significant length heterogeneity, ranging from sparse short-term interactions to rich long-term histories. While lo…