SOURCE-LINKED INTELLIGENCE

Task-Specific Prompt with Global Context for Multi-Task Graph Pre-Training

arXiv · AI, language, vision and robotics · article · Aug 30, 2026 · UTC

Graph prompt learning is an effective paradigm to adapt pre-trained graph models to downstream tasks in low-resource scenarios. However, existing multi-task graph pre-training frameworks generally use randomly initialized prompts, leading to poor alignment between the prompt space, pretext objectives and graph structural characteristics. This greatly weakens the task relevance, structural awareness and transferability of prompt representations. To address this challenge, we propose TPGC, a dual-prior prompt initialization solution that explicitly models the synergy between task prior and struc

Read original source ↗ Open in workspace

recordType

paper

region

Global