WSNET integrates weak-label classification and contrastive losses to learn node representations, outperforming baselines on weakly labeled graphs.
Justice in misinformation detection systems: An analysis of algorithms, stakeholders, and potential harms
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Weak Supervision for Real World Graphs
WSNET integrates weak-label classification and contrastive losses to learn node representations, outperforming baselines on weakly labeled graphs.