Summary of Gofa: a Generative One-for-all Model For Joint Graph Language Modeling, by Lecheng Kong et al.
GOFA: A Generative One-For-All Model for Joint Graph Language Modelingby Lecheng Kong, Jiarui Feng, Hao…
GOFA: A Generative One-For-All Model for Joint Graph Language Modelingby Lecheng Kong, Jiarui Feng, Hao…
The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisitedby Floriano Tori,…
Graph Neural Network Causal Explanation via Neural Causal Modelsby Arman Behnam, Binghui WangFirst submitted to…
TinyGraph: Joint Feature and Node Condensation for Graph Neural Networksby Yezi Liu, Yanning ShenFirst submitted…
Explaining Graph Neural Networks for Node Similarity on Graphsby Daniel Daza, Cuong Xuan Chu, Trung-Kien…
Advanced Financial Fraud Detection Using GNN-CL Modelby Yu Cheng, Junjie Guo, Shiqing Long, You Wu,…
Graph Neural Networks and Deep Reinforcement Learning Based Resource Allocation for V2X Communicationsby Maoxin Ji,…
Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attentionby Tongzhou Liao, Barnabás PóczosFirst submitted to…
G-Adaptivity: optimised graph-based mesh relocation for finite element methodsby James Rowbottom, Georg Maierhofer, Teo Deveney,…
SSP-GNN: Learning to Track via Bilevel Optimizationby Griffin Golias, Masa Nakura-Fan, Vitaly AblavskyFirst submitted to…