11 citations · 11 across the 3 of their papers we have counts for
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cs.IR2025
LLM-Powered Nuanced Video Attribute Annotation for Enhanced Recommendations
Boyuan Long, Yueqi Wang, Hiloni Mehta +10
This paper presents a case study on deploying Large Language Models (LLMs) as an advanced "annotation" mechanism to achieve nuanced content understanding (e.g., discerning content…
cs.IR2024
LLMs for User Interest Exploration in Large-scale Recommendation Systems
Jianling Wang, Haokai Lu, Yifan Liu +9
Traditional recommendation systems are subject to a strong feedback loop by learning from and reinforcing past user-item interactions, which in turn limits the discovery of novel u…
cs.IR2023★ 11 cited
Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders
Yueqi Wang, Yoni Halpern, Shuo Chang +9
Sequential recommenders have been widely used in industry due to their strength in modeling user preferences. While these models excel at learning a user's positive interests, less…