2 citations · 2 across the 4 of their papers we have counts for
4 papers
CreaMem: A Scene-Aware Memory Architecture for Personalized Agents
Qixuan Sun, Yue Que, Bowei He +4
Long-term memory is a core capability for personalized LLM agents. To support it, existing memory systems organize information using various criteria such as topic segments or summ…
LLM-as-a-Judge for Reliable and Explainable Offline Evaluation in Top-K Recommendation
Yue Que, Junyi Zhou, Xiaokun Zhang +3
Recommendation evaluation plays a crucial role in guiding the refinement and deployment of recommender systems. Most existing trials rely on offline evaluation using Top-K metrics…
Causality-aware Graph Aggregation Weight Estimator for Popularity Debiasing in Top-K Recommendation
Yue Que, Yingyi Zhang, Xiangyu Zhao +1
Graph-based recommender systems leverage neighborhood aggregation to generate node representations, which is highly sensitive to popularity bias, resulting in an echo effect during…
Learning Binarized Representations with Pseudo-positive Sample Enhancement for Efficient Graph Collaborative Filtering
Yankai Chen, Yue Que, Xinni Zhang +2
Learning vectorized embeddings is fundamental to many recommender systems for user-item matching. To enable efficient online inference, representation binarization, which embeds la…