Transductive Sharpening adds an entropy-minimization term on unlabeled-node predictions to the training objective for graph node classification.
NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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QUIET is a hierarchical RVQ-based graph tokenizer with a learned level-weighting gate; it improves several benchmarks but not consistently against the strongest baselines.
citing papers explorer
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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.
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A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation Learning
QUIET is a hierarchical RVQ-based graph tokenizer with a learned level-weighting gate; it improves several benchmarks but not consistently against the strongest baselines.