3 papers
cs.IR2026
On-Device Large Language Models for Sequential Recommendation
Xin Xia, Hongzhi Yin, Shane Culpepper
On-device recommendation is critical for a number of real-world applications, especially in scenarios that have agreements on execution latency, user privacy, and robust functional…
cs.IR2025
On-Device Recommender Systems: A Comprehensive Survey
Hongzhi Yin, Liang Qu, Tong Chen +6
Recommender systems have been widely deployed in various real-world applications to help users identify content of interest from massive amounts of information. Traditional recomme…
cs.IR2025
Breaking the Clusters: Uniformity-Optimization for Text-Based Sequential Recommendation
Wuhan Chen, Zongwei Wang, Min Gao +3
Traditional sequential recommendation (SR) methods heavily rely on explicit item IDs to capture user preferences over time. This reliance introduces critical limitations in cold-st…