3 papers
cs.IR2026
Disagreement as Signals: Dual-view Calibration for Sequential Recommendation Denoising
Sijia Li, Min Gao, Zongwei Wang +3
Sequential recommendation seeks to model the evolution of user interests by capturing temporal user intent and item-level transition patterns. Transformer-based recommenders demons…
cs.IR2026
Green-Red Watermarking for Recommender Systems
Lei Zhou, Min Gao, Zongwei Wang +2
The widespread open-sourcing of advanced recommendation algorithms and the rising threat of model extraction attacks have made safeguarding the intellectual property of recommender…
cs.IR2025
Breaking the Clusters: Uniformity-Optimization for Text-Based Sequential Recommendation
Wuhan Chen, Zongwei Wang, Min Gao +3
Traditional sequential recommendation (SR) methods heavily rely on explicit item IDs to capture user preferences over time. This reliance introduces critical limitations in cold-st…