6 papers · 1 filter
Post-hoc Provider Fairness Adaptation via Hierarchical Exposure Alignment
Jingzhi Li, Zhiyong Cheng, Richang Hong +1
Provider exposure fairness is crucial for sustaining a healthy content ecosystem and preventing monopolization in recommender systems. Yet, most existing methods either incorporate…
Modeling Stage-wise Evolution of User Interests for News Recommendation
Zhiyong Cheng, Yike Jin, Zhijie Zhang +3
Personalized news recommendation is highly time-sensitive, as user interests are often driven by emerging events, trending topics, and shifting real-world contexts. These dynamics…
From Atom to Community: Structured and Evolving Agent Memory for User Behavior Modeling
Yuxin Liao, Le Wu, Min Hou +3
User behavior modeling lies at the heart of personalized applications like recommender systems. With LLM-based agents, user preference representation has evolved from latent embedd…
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…
Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias
Miaomiao Cai, Lei Chen, Yifan Wang +5
Collaborative Filtering (CF) typically suffers from the significant challenge of popularity bias due to the uneven distribution of items in real-world datasets. This bias leads to…
Multimodality Invariant Learning for Multimedia-Based New Item Recommendation
Haoyue Bai, Le Wu, Min Hou +5
Multimedia-based recommendation provides personalized item suggestions by learning the content preferences of users. With the proliferation of digital devices and APPs, a huge numb…