3 papers
cs.IR2026
Bridging Semantic Understanding and Popularity Bias with LLMs
Renqiang Luo, Dong Zhang, Yupeng Gao +5
Semantic understanding of popularity bias is a crucial yet underexplored challenge in recommender systems, where popular items are often favored at the expense of niche content. Mo…
cs.IR2025
Modeling Item-Level Dynamic Variability with Residual Diffusion for Bundle Recommendation
Dong Zhang, Lin Li, Ming Li +4
Existing solutions for bundle recommendation (BR) have achieved remarkable effectiveness for predicting the user's preference for prebuilt bundles. However, bundle-item (B-I) affil…
cs.IR2024
A Survey on Bundle Recommendation: Methods, Applications, and Challenges
Meng Sun, Lin Li, Ming Li +5
In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by…