![[2606.03290] Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective](/static/img/curated/desks/afbytes-tech.png)
[2606.03290] Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
Abstract page for arXiv paper 2606.03290: Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
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[2606.03495] HiSE: A Lightweight Hierarchical Semantic Explainer for Heterogeneous Graph Neural Networks
Abstract page for arXiv paper 2606.03495: HiSE: A Lightweight Hierarchical Semantic Explainer for Heterogeneous Graph Neural Networks
[2505.20840] Aggregation Buffer: Revisiting DropEdge with a New Parameter Block
Abstract page for arXiv paper 2505.20840: Aggregation Buffer: Revisiting DropEdge with a New Parameter Block
[2605.30486] Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting
Abstract page for arXiv paper 2605.30486: Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting
[2605.31500] On Efficient Scaling of GNNs via IO-Aware Layers Implementations
Abstract page for arXiv paper 2605.31500: On Efficient Scaling of GNNs via IO-Aware Layers Implementations
[2605.28524] Let Relations Speak: An End-to-End LLM-GNN Soft Prompt Framework for Fraud Detection
Abstract page for arXiv paper 2605.28524: Let Relations Speak: An End-to-End LLM-GNN Soft Prompt Framework for Fraud Detection