Tongze Zhang

A Lightweight Plastic-Memory Framework for Graph Few-Shot Class-Incremental Learning

This paper proposes a novel lightweight plastic-memory framework specifically designed for few-shot incremental learning on graphs, featuring an innovative evolving micro-clustering structure that dynamically updates representations of class prototypes, sub-prototypes, and their interaction weights.