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cs.IR2025
Generating Negative Samples for Multi-Modal Recommendation
Yanbiao Ji, Dan Luo, Chang Liu +6
Multi-modal recommender systems (MMRS) have gained significant attention due to their ability to leverage information from various modalities to enhance recommendation quality. How…
cs.IR2025
How Does Topology Bias Distort Message Passing? A Dirichlet Energy Perspective
Yanbiao Ji, Yue Ding, Dan Luo +4
Graph-based recommender systems have achieved remarkable effectiveness by modeling high-order interactions between users and items. However, such approaches are significantly under…
cs.IR2024
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation
Yue Ding, Yanbiao Ji, Xun Cai +7
In modern recommender systems, especially in e-commerce, predicting multiple targets such as click-through rate (CTR) and post-view conversion rate (CTCVR) is common. Multi-task re…