3 papers
cs.LG2026
Informative Graph Structure Learning
Shen Han, Zhiyao Zhou, Jiawei Chen +6
The quality of graph-structured data is fundamental to the success of modern graph analysis techniques such as Graph Neural Networks (GNNs). However, real-world graph data is often…
cs.IR2025
Rankformer: A Graph Transformer for Recommendation based on Ranking Objective
Sirui Chen, Shen Han, Jiawei Chen +6
Recommender Systems (RS) aim to generate personalized ranked lists for each user and are evaluated using ranking metrics. Although personalized ranking is a fundamental aspect of R…
cs.LG2025
Uncertainty-Aware Graph Structure Learning
Shen Han, Zhiyao Zhou, Jiawei Chen +6
Graph Neural Networks (GNNs) have become a prominent approach for learning from graph-structured data. However, their effectiveness can be significantly compromised when the graph…