Papers with GLN

1 papers
‘Hello, World!’: Making GNNs Talk with LLMs (2025.findings-emnlp)

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Challenge: graph neural networks have shown remarkable performance across diverse graph-related tasks, but their high-dimensional hidden representations render them black boxes.
Approach: They propose a graph-based neural network with hidden representations in the form of human-readable text.
Outcome: The proposed GNN outperforms existing LLM-based baseline methods on node classification and link prediction.

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