3 papers
cs.IR2026
FedUTR: Federated Recommendation with Augmented Universal Textual Representation for Sparse Interaction Scenarios
Kang Fu, Honglei Zhang, Zikai Zhang +5
Federated recommendations (FRs) have emerged as an on-device privacy-preserving paradigm, attracting considerable attention driven by rising demands for data security. Existing FRs…
cs.IR2026
Following the TRAIL: Predicting and Explaining Tomorrow's Hits with a Fine-Tuned LLM
Yinan Zhang, Zhixi Chen, Jiazheng Jing +1
Large Language Models (LLMs) have been widely applied across multiple domains for their broad knowledge and strong reasoning capabilities. However, applying them to recommendation…
cs.IR2025
Does Multimodality Improve Recommender Systems as Expected? A Critical Analysis and Future Directions
Hongyu Zhou, Yinan Zhang, Aixin Sun +1
Multimodal recommendation systems are increasingly popular for their potential to improve performance by integrating diverse data types. However, the actual benefits of this integr…