Universal Prompt Tuning for Graph Neural Networks

arXiv:2209.15240v5 Announce Type: replace
Abstract: In recent years, prompt tuning has sparked a research surge in adapting pre-trained models. Unlike the unified pre-training strategy employed in the language field, the graph field exhibits diverse pre-training strategies, posing challenges in designing appropriate prompt-based tuning methods for graph neural networks. While some pioneering work has devised specialized prompting functions for models that employ edge prediction as their pre-training tasks, these methods are limited to specific pre-trained GNN models and lack broader applicability. …

abstract arxiv challenges cs.ai cs.lg designing diverse graph graph neural networks language networks neural networks pre-trained models pre-training prompt prompt tuning research strategies strategy the graph training type universal work