Continual-GraphLLM: Dynamic Graph Large Language Model with Invariance Regularized Adaptive Multi-Scale Experts
A novel Continual Learning Dynamic Graph LLM framework (Continual-GraphLLM) is proposed to continually adapt to incoming patterns by routing them to experts specialized in similar past patterns, while mitigating the overwriting of previously learned patterns by assigning new experts to unseen patterns.