3 citations · 3 across the 3 of their papers we have counts for
4 papers
Mend the Measurement Gap: Latent User Preference Modeling for Short-Form Video Recommendation
Shuo Chang, Yueqi Wang, Zihuan Diao +7
Recommender systems rely heavily on heterogeneous behavioral feedback to infer user preference. Although abundant, these signals are imperfect measurements: the same observed behav…
Soft Curriculum Learning for Optimizing Fresh and Generalized Recommendations
Arnab Bhadury, Siyan Zheng, Anlan Yu +6
Large-scale recommender systems, particularly short-form video platforms, are often bottlenecked by massive popularity feedback loops. In such environments, as models recommend pop…
Balancing Fine-tuning and RAG: A Hybrid Strategy for Dynamic LLM Recommendation Updates
Changping Meng, Hongyi Ling, Jianling Wang +9
Large Language Models (LLMs) empower recommendation systems through their advanced reasoning and planning capabilities. However, the dynamic nature of user interests and content po…
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…