3 papers
cs.IR2026
One Graph, Multiple Gains: Single High-Quality Item-Item Graph for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Ziyue Peng +6
Multimodal recommendation leverages item multimodal features alongside collaborative signals to capture user preferences. While item-item graphs have become a key building block in…
cs.LG2026
Fisher-Routed Mixture of Experts for Federated Class-Incremental Learning
Wenhao Yuan, Chenchen Lin, Jian Chen +3
Federated Learning (FL) emerged as a promising distributed machine learning paradigm. However, extending FL to the class incremental learning scenarios introduces unique challenges…
cs.LG2025
Multi-modal Dynamic Proxy Learning for Personalized Multiple Clustering
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
Multiple clustering aims to discover diverse latent structures from different perspectives, yet existing methods generate exhaustive clusterings without discerning user interest, n…