4 papers
RMBRec: Robust Multi-Behavior Recommendation towards Target Behaviors
Miaomiao Cai, Zhijie Zhang, Junfeng Fang +3
Multi-behavior recommendation faces a critical challenge in practice: auxiliary behaviors (e.g., clicks, carts) are often noisy, weakly correlated, or semantically misaligned with…
Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning
Miaomiao Cai, Min Hou, Lei Chen +4
Collaborative Filtering~(CF) plays a crucial role in modern recommender systems, leveraging historical user-item interactions to provide personalized suggestions. However, CF-based…
I-MRec: Invariant Learning with Information Bottleneck for Incomplete Modality Recommendation
Huilin Chen, Miaomiao Cai, Fan Liu +3
Multimodal recommender systems (MRS) improve recommendation performance by integrating complementary semantic information from multiple modalities. However, the assumption of compl…
Graph-Structured Driven Dual Adaptation for Mitigating Popularity Bias
Miaomiao Cai, Lei Chen, Yifan Wang +3
Popularity bias is a common challenge in recommender systems. It often causes unbalanced item recommendation performance and intensifies the Matthew effect. Due to limited user-ite…