1 citations · 2 across the 5 of their papers we have counts for
7 papers
Federated Semantic Residuals for Multimodal Recommendation
Zhiwei Li, Guodong Long, Chengqi Zhang +1
Federated Recommendation Systems (FedRSs) learn collaborative scores from interaction histories on device and rank items by them, so a higher score means a higher rank. Item text a…
Symmetric Bases and Embeddings in Musielak--Orlicz Sequence Spaces under
Valentin Georgiev, Boyan Zlatanov
We study isomorphic embeddings into Musielak-Orlicz sequence spaces \(\ell_Φ\), where the normalized generating sequence \(Φ=\{ϕ_n\}\) satisfies the \(δ_2\) condition. Using admiss…
Content Depth Matters in Short-Video Recommendation: Rethinking the Attention Economy
Liwei Deng, Jing Jiang, Zhiwei Li +2
Driven by the attention economy, short-video Recommender Systems (RSs) are primarily optimized to maximize user engagement by promoting videos that capture attention within seconds…
Tag-Enriched Multi-Attention with Large Language Models for Cross-Domain Sequential Recommendation
Wangyu Wu, Xuhang Chen, Zhenhong Chen +5
Cross-Domain Sequential Recommendation (CDSR) plays a crucial role in modern consumer electronics and e-commerce platforms, where users interact with diverse services such as books…
A Survey of Personalized Federated Foundation Models for Privacy-Preserving Recommendation
Zhiwei Li, Guodong Long, Chunxu Zhang +3
Integrating Foundation Models (FMs) into recommendation systems is an emerging and promising research direction. However, centralized paradigms face growing pressure from privacy c…
A Tutorial of Personalized Federated Recommender Systems: Recent Advances and Future Directions
Jing Jiang, Chunxu Zhang, Honglei Zhang +3
Personalization stands as the cornerstone of recommender systems (RecSys), striving to sift out redundant information and offer tailor-made services for users. However, the convent…
Navigating the Future of Federated Recommendation Systems with Foundation Models
Zhiwei Li, Guodong Long, Chunxu Zhang +3
Federated Recommendation Systems (FRSs) offer a privacy-preserving alternative to traditional centralized approaches by decentralizing data storage. However, they face persistent c…