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Graph Attention Network

techniqueactiveprovisionalgraph-attention-network-73e2ad41·1 events·first seen 18h ago

Aliases: Graph Attention Network

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4arXiv · cs.AI·18h ago·source ↗

PromptGNN-sim: Bidirectional GNN-LLM fusion framework for text-attributed graph learning

Researchers introduce PromptGNN-sim, a bidirectional structure-semantic fusion framework that jointly trains a Graph Attention Network and an LLM for text-attributed graph learning. The system uses GAT-based neighborhood selection to generate structure-aware prompts for the LLM, with cross-modal contrastive learning and cross-attention aligning both components during training. Evaluated on six datasets including Cora, Pubmed, and WikiCS, it outperforms classical GNNs, standalone LLMs, and prior GNN-LLM fusion methods on cross-task transfer, cross-dataset generalization, and sparse perturbation settings.