EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
Finding Global Homophily in Graph Neural Networks When Meeting Het- erophily
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 2years
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Transductive Sharpening adds an entropy-minimization term on unlabeled-node predictions to the training objective for graph node classification.
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Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks
EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
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Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification
Transductive Sharpening adds an entropy-minimization term on unlabeled-node predictions to the training objective for graph node classification.