4 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.IR2023★ 4 cited
Frequency Enhanced Hybrid Attention Network for Sequential Recommendation
Xinyu Du, Huanhuan Yuan, Pengpeng Zhao +4
The self-attention mechanism, which equips with a strong capability of modeling long-range dependencies, is one of the extensively used techniques in the sequential recommendation…
cs.IR2023★ 1 cited
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation
Hanwen Du, Huanhuan Yuan, Pengpeng Zhao +4
Sequential recommendation aims to capture users' dynamic interest and predicts the next item of users' preference. Most sequential recommendation methods use a deep neural network…
cs.IR2023
Meta-optimized Contrastive Learning for Sequential Recommendation
Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao +4
Contrastive Learning (CL) performances as a rising approach to address the challenge of sparse and noisy recommendation data. Although having achieved promising results, most exist…