2 papers
cs.LG2026
Formalizing and Mitigating Structural Distortion in LLM Attention for Graph Reasoning
Donald Loveland, Puja Trivedi, Ari Weinstein +2
Large Language Models (LLMs) have shown promise for reasoning over Text-Attributed Graphs (TAGs). However, applying LLMs to graphs requires linearizing their structure into sequenc…
cs.LG2023
Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance
Donald Loveland, Rajmonda Caceres
Graph Neural Network (GNN) research has produced strategies to modify a graph's edges using gradients from a trained GNN, with the goal of network design. However, the factors whic…