#graph neural networks
Aug 2026
Taking lessons from history: Memory Augmented Self Distillation for graph neural networks
This study introduces a novel memory-augmented self-learning framework that extracts and provides diverse learning sources for adaptive knowledge distillation from the student model itself, resulting in a 2.5-6% increase in accuracy across various benchmark datasets compared to current GNN training and self-distillation methods.
Saurabh Sharma, Souvik Chowdhury, Joydeep Chandra
· Data mining and knowledge di... · 0 citations