3 papers
cs.IR2025
Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs
Yuhao Wang, Junwei Pan, Xinhang Li +6
Sequential recommendation (SR) aims to capture users' dynamic interests and sequential patterns based on their historical interactions. Recently, the powerful capabilities of large…
cs.IR2025
LEADRE: Multi-Faceted Knowledge Enhanced LLM Empowered Display Advertisement Recommender System
Fengxin Li, Yi Li, Yue Liu +11
Display advertising provides significant value to advertisers, publishers, and users. Traditional display advertising systems utilize a multi-stage architecture consisting of retri…
cs.IR2025
Measure Domain's Gap: A Similar Domain Selection Principle for Multi-Domain Recommendation
Yi Wen, Yue Liu, Derong Xu +9
Multi-Domain Recommendation (MDR) achieves the desirable recommendation performance by effectively utilizing the transfer information across different domains. Despite the great su…