Author

Lei Sang

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Preprint Oct 2026

Bezier-Guided Adaptive Flow for Cross-domain Sequential Recommendation

Cross-domain sequential recommendation aims to alleviate data sparsity and cold-start problems by transferring useful preference knowledge across domains. However, users exhibit varying degrees of preference consistency across domains, while existing methods often rely on global alignment objectives or coarse-grained t...

Ziang Lu, Yu Zhang, Xin-Zhe Jiang et al. · 0 citations

Oct 2026

Semantic Augmented Multiview Graph Learning With Frequency-Aware Propagation for Recommendation

Graph neural networks (GNNs) have been widely adopted in collaborative filtering to model higher order relationships between users and items. However, existing methods mainly focus on interaction-based structures and neglect the explicit modeling of semantic relations among users and among items. Within these graph str...

Yi-Xin Liu, Yu Zhang, Lei Sang et al. · IEEE Transactions on Computa... · 0 citations

#graph neural networks Oct 2026

Heterogeneous Debiasing Contrastive Learning for Graph Recommendation

Heterogeneous graph neural networks (HGNNs) have demonstrated exceptional capabilities in modeling complex relationships for recommendation tasks. Their integration with contrastive learning (CL) has recently garnered significant attention due to its ability to effectively capture both structural and semantic features,...

Lei Sang, Jia-Hao Cheng, Lin Mu et al. · IEEE Transactions on Systems... · 0 citations