3 papers
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.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.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…