7 citations · 13 across the 10 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.IR2024
EXIT: An EXplicit Interest Transfer Framework for Cross-Domain Recommendation
Lei Huang, Weitao Li, Chenrui Zhang +3
Cross-domain recommendation has attracted substantial interest in industrial apps such as Meituan, which serves multiple business domains via knowledge transfer and meets the diver…
cs.IR2024★ 2 cited
Sequence-level Semantic Representation Fusion for Recommender Systems
Lanling Xu, Zhen Tian, Bingqian Li +4
With the rapid development of recommender systems, there is increasing side information that can be employed to improve the recommendation performance. Specially, we focus on the u…
cs.IR2024★ 7 cited
Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis
Lanling Xu, Junjie Zhang, Bingqian Li +4
Recently, Large Language Models~(LLMs) such as ChatGPT have showcased remarkable abilities in solving general tasks, demonstrating the potential for applications in recommender sys…