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Heterophilic Text-attributed Graph Benchmark (HeTGB)

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1papers using it
2025first seen

The Heterophilic Text-attributed Graph Benchmark (HeTGB) is a comprehensive benchmark consisting of five real-world heterophilic graph datasets enriched with textual descriptions, used to systematically evaluate graph neural networks, pre-trained language models, and co-training methods on the node classification task.

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Papers using Heterophilic Text-attributed Graph Benchmark (HeTGB) (1)

Heterophilic Text-attributed Graph Benchmark (HeTGB) — datasets — graph-learning