Author

Jianhua Zhao

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Open access 2026

Large Language Model Semantic-Guided Counterfactual Data Augmentation for Cross-Domain Sequential Recommendation

Cross-domain sequential recommendation leverages source-domain interactions to alleviate target-domain sparsity, yet existing methods struggle with semantic gaps, insufficient training signals under extreme sparsity, and negative transfer caused by user heterogeneity. To address these issues, this paper proposes LLM-CF...

Ning Liu, Jian-Hua Zhao, Rong-Hua Zhao · IEEE Access · 0 citations

Open access 2026

Robust Cross-Domain Sequential Recommendation Driven by Causal Disentanglement and Counterfactual Generation

Sequential recommendation systems are confronted with the dual challenges of data sparsity and domain bias. Especially in cross-domain scenarios, user interests are deeply coupled with domain-specific noise, which severely restricts recommendation performance. Targeted at improving the robustness of cross-domain sequen...

Jianhua Zhao, Ning Liu, Ronghua Zhao · IEEE Access · 0 citations