Graph Classification On Upfd Gos
Metriken
Accuracy (%)
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| UPFD-SAGE | 97.54 | User Preference-aware Fake News Detection |
| HGFND | 97.46±0.30 | Nothing Stands Alone: Relational Fake News Detection with Hypergraph Neural Networks |
| UPFD-GAT | 96.52 | User Preference-aware Fake News Detection |
| UPFD-GCNFN | 96.11 | User Preference-aware Fake News Detection |
| GCNFN | 95.90 | User Preference-aware Fake News Detection |
| UPFD-GCN | 95.11 | User Preference-aware Fake News Detection |
| GNNCL | 93.60 | User Preference-aware Fake News Detection |
| UPFD-BiGCN | 91.27 | User Preference-aware Fake News Detection |
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