Xavier Bresson

Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning

2023 · arXiv (Cornell University)

Representation learning on text-attributed graphs (TAGs) has become a critical research problem in recent years. A typical example of a TAG is a paper citation graph, where the text of each paper serves as node …

Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classifications

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

Graph Neural Networks (GNNs) have become the preferred tool to process graph data, with their efficacy being boosted through graph data augmentation techniques. Despite the evolution of augmentation methods, issues like graph property distortions and …

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

2017 · Neural Information Processing Systems

Matrix completion models are among the most common formulations of recommender systems. Recent works have showed a boost of performance of these techniques when introducing the pairwise relationships between users/items in the form of graphs, …