Papers with HGNNs

2 papers
HyperIDP: Customizing Temporal Hypergraph Neural Networks for Multi-Scale Information Diffusion Prediction (2025.coling-main)

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Challenge: Existing studies on information diffusion prediction have focused on both macroscopic and microscopic scales.
Approach: They propose a hypergraph-based model that manages both macroscopic and microscopic diffusion predictions.
Outcome: The proposed model outperforms baseline models on both macroscopic and microscopic tasks.
LLM-Empowered Class Imbalanced Graph Prompt Learning for Online Drug Trafficking Detection (2025.findings-acl)

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Challenge: Existing approaches to combat illicit drug trafficking are impractical due to the scarcity of labeled samples and imbalance of classes.
Approach: They propose a Large Language Model-empowered Heterogeneous Graph Prompt Learning framework for illicit drug trafficking detection that leverages LLM to facilitate heterogeneous graph neural networks to effectively identify minority classes.
Outcome: The proposed framework is able to identify minority classes in class-imbalanced scenarios.

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