The paper derives a per-class generalization bound for imbalanced transductive node classification and introduces UPL, a pseudo-labeling algorithm that filters minority-class pseudo-labels by entropy variance across edge-perturbed graphs.
Confidence may cheat: Self-training on graph neural networks under distribution shift
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
UPL: Uncertainty-aware Pseudo-labeling for Imbalance Transductive Node Classification
The paper derives a per-class generalization bound for imbalanced transductive node classification and introduces UPL, a pseudo-labeling algorithm that filters minority-class pseudo-labels by entropy variance across edge-perturbed graphs.