2 citations · 2 across the 15 of their papers we have counts for
3 papers · 1 filter
Graph Neural Networks Are Not Continuous Across Graph Resolutions
Christian Koke, Yuesong Shen, Abhishek Saroha +4
We show that contrary to conventional wisdom in the community, graph neural networks (GNNs) are not continuous with respect to all natural modes of graph convergence. As a result,…
A Mechanistic Analysis of Looped Reasoning Language Models
Hugh Blayney, Álvaro Arroyo, Johan Obando-Ceron +4
Reasoning has become a central capability in large language models. Recent research has shown that reasoning performance can be improved by looping an LLM's layers in the latent di…
Can Graph Foundation Models Generalize Over Architecture?
Benjamin Gutteridge, Michael Bronstein, Xiaowen Dong
Graph foundation models (GFMs) have recently attracted interest due to the promise of graph neural network (GNN) architectures that generalize zero-shot across graphs of arbitrary…