4 papers
A Cross-graph Tuning-free GNN Prompting Framework
Yaqi Chen, Shixun Huang, Ryan Twemlow +6
GNN prompting aims to adapt models across tasks and graphs without requiring extensive retraining. However, most existing graph prompt methods still require task-specific parameter…
BIOME-Bench: A Benchmark for Biomolecular Interaction Inference and Multi-Omics Pathway Mechanism Elucidation from Scientific Literature
Sibo Wei, Peng Chen, Lifeng Dong +7
Multi-omics studies often rely on pathway enrichment to interpret heterogeneous molecular changes, but pathway enrichment (PE)-based workflows inherit structural limitations of pat…
A Community-Enhanced Graph Representation Model for Link Prediction
Lei Wang, Darong Lai
Although Graph Neural Networks (GNNs) have become the dominant approach for graph representation learning, their performance on link prediction tasks does not always surpass that o…
Edge-free but Structure-aware: Prototype-Guided Knowledge Distillation from GNNs to MLPs
Taiqiang Wu, Zhe Zhao, Jiahao Wang +4
Distilling high-accuracy Graph Neural Networks (GNNs) to low-latency multilayer perceptions (MLPs) on graph tasks has become a hot research topic. However, conventional MLP learnin…