MultiGPrompt for multi-task pre-training and prompting on graphs

• Main Authors: YU, Xingtong, ZHOU, Chang, FANG, Yuan, ZHAN, Xinming
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Graph learning; prompting; multi-task; few-shot learning; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8711; https://ink.library.smu.edu.sg/context/sis_research/article/9714/viewcontent/Multi_task_Graph_Prompt__Camera_ready_.pdf
• Institution: Singapore Management University

Graph Neural Networks (GNNs) have emerged as a mainstream technique for graph representation learning. However, their efficacy within an end-to-end supervised framework is significantly tied to the availability of task-specific labels. To mitigate labeling costs and enhance robustness in few-shot se...