3 citations · 4 across the 3 of their papers we have counts for
4 papers
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…
Reducing Symbiosis Bias Through Better A/B Tests of Recommendation Algorithms
Jennifer Brennan, Yahu Cong, Yiwei Yu +6
It is increasingly common in digital environments to use A/B tests to compare the performance of recommendation algorithms. However, such experiments often violate the stable unit…