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cs.LG2026
Topological Deep Learning Challenge 2026: Bridging the Gap
Guillermo Bernárdez, Lev Telyatnikov, Mathilde Papillon +68
This paper describes the 2026 edition of the Topological Deep Learning Challenge: Bridging the Gap, hosted at the second Topology, Algebra, and Geometry in Data Science (TAG-DS) Co…
cs.LG2026
Do Sheaf Neural Networks Use Holonomy? A Measure--Intervene--Control Study
Ankit Grover, Rémi Bourgerie
Geometric architectures are often motivated by internal mechanisms, but accuracy alone does not show whether predictions use them. In Sheaf Neural Networks (SNNs), edge transports…
cs.LG2026
Is One Token All It Takes? Graph Pooling Tokens for LLM-based GraphQA
Ankit Grover, Lodovico Giaretta, Rémi Bourgerie +1
The integration of Graph Neural Networks (GNNs) with Large Language Models (LLMs) has emerged as a promising paradigm for Graph Question Answering (GraphQA). However, effective met…