3 papers
cs.LG2026
From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context
Peyman Baghershahi, Gregoire Fournier, Pranav Nyati +1
Graph Neural Networks (GNNs) have emerged as powerful tools for learning over structured data, including text-attributed graphs (TAGs), which are common in domains such as citation…
cs.LO2025
A Game for Counting Logic Formula Size and an Application to Linear Orders
Gregoire Fournier, György Turán
Ehrenfeucht-Fraïssé (EF) games are a basic tool in finite model theory for proving definability lower bounds, with many applications in complexity theory and related areas. They…
cs.LG2025
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
Gregoire Fournier, Sourav Medya
Graph neural networks (GNNs) have been widely used in various domains such as social networks, molecular biology, or recommendation systems. Concurrently, different explanations me…