3 papers
cs.CL2025
iAgent: LLM Agent as a Shield between User and Recommender Systems
Wujiang Xu, Yunxiao Shi, Zujie Liang +6
Traditional recommender systems usually take the user-platform paradigm, where users are directly exposed under the control of the platform's recommendation algorithms. However, th…
cs.IR2025
PersonaX: A Recommendation Agent Oriented User Modeling Framework for Long Behavior Sequence
Yunxiao Shi, Wujiang Xu, Zeqi Zhang +3
User profile embedded in the prompt template of personalized recommendation agents play a crucial role in shaping their decision-making process. High-quality user profiles are esse…
cs.IR2025
FedPCL-CDR: A Federated Prototype-based Contrastive Learning Framework for Privacy-Preserving Cross-domain Recommendation
Li Wang, Qiang Wu, Min Xu
Cross-domain recommendation (CDR) aims to improve recommendation accuracy in sparse domains by transferring knowledge from data-rich domains. However, existing CDR approaches often…