Xinming Zhang

MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs

2024

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 …

JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation

2025 · arXiv (Cornell University)

The discovery of new molecules based on the original chemical molecule distributions is of great importance in medicine. The graph transformer, with its advantages of high performance and scalability compared to traditional graph networks, has …