Graph Anomaly Detection on CiteSeer
86.18AUPRCN2NSC
Evaluation results
| Method | Links | ||
|---|---|---|---|
| N2NSCMethodology=Ours2026.06 | 86.18 | — | |
| REFI-GADTraining Setup=Training on Group 22026.05 | 70.91 | — | |
| GraphSAGEMethodology=GNN-based2026.06 | 68.1 | — | |
| GCNMethodology=GNN-based2026.06 | 67.37 | — | |
| TAPEMethodology=LLM-integrated2026.06 | 63.26 | — | |
| GINMethodology=GNN-based2026.06 | 62.39 | — | |
| BWGNNMethodology=GNN-based2026.06 | 61.62 | — | |
| RFGraphMethodology=GNN-based2026.06 | 60.47 | — | |
| TERGAD2026.05 | 60.07 | 95.78 | |
| XGBGraphMethodology=GNN-based2026.06 | 56.3 | — | |
| EvoFGCategory=Generalist method, Setting=Zero-shot2026.02 | 52.09 | 91.57 | |
| IA-GGADTraining Setup=Training on Group 22026.05 | 48.82 | — | |
| ARCCategory=Generalist method, Setting=Zero-shot2026.02 | 47.79 | 90.82 | |
| ARCTraining Setup=Training on Group 22026.05 | 47.56 | — | |
| PC-GNNMethodology=GNN-based2026.06 | 46.19 | — | |
| AHFANTraining Setup=Training on Group 22026.05 | 45.16 | — | |
| GADNR2026.05 | 43.98 | 75.04 | |
| SmoothGNNTraining Setup=Training on Group 22026.05 | 41.39 | — | |
| GAD-MoREEvaluation Protocol=0-shot2026.02 | 40.15 | — | |
| GHRNMethodology=GNN-based2026.06 | 39.81 | — | |
| AHFAN2026.05 | 38.08 | 87.43 | |
| DOMINANT2026.05 | 34.86 | 92.85 | |
| ARCEvaluation Protocol=10-shot2026.02 | 30.93 | — | |
| FIAD2026.05 | 28.24 | 87.5 | |
| GATMethodology=GNN-based2026.06 | 27.49 | — | |
| GCNAE2026.05 | 23.91 | 71.95 | |
| GAAN2026.05 | 23.86 | 70.76 | |
| MLPAE2026.05 | 23.73 | 72.1 | |
| AnomalyDAE2026.05 | 23.73 | 72.08 | |
| CoLLMethodology=LLM-integrated2026.06 | 17.49 | — | |
| UNPromptMethodology=LLM-integrated2026.06 | 17.47 | — | |
| BWGNNCategory=Supervised method, Setting=Zero-shot2026.02 | 16.06 | 67.72 | |
| AlignGADType=Generalist GAD2026.06 | 15.9 | 69.9 | |
| CoLATraining Setup=Training on Group 22026.05 | 15.34 | — | |
| CHRNTraining Setup=Training on Group 22026.05 | 15.01 | — | |
| CoLA2026.05 | 14.28 | 71.01 | |
| GAAPMethodology=GNN-based2026.06 | 12.3 | — | |
| GHRNCategory=Supervised method, Setting=Zero-shot2026.02 | 12.02 | 61.53 | |
| GGADTraining Setup=Training on Group 22026.05 | 11.12 | — | |
| UNPromptTraining Setup=Training on Group 22026.05 | 10.41 | — | |
| ConsisGADMethodology=LLM-integrated2026.06 | 9.93 | — | |
| PMPMethodology=GNN-based2026.06 | 9.45 | — | |
| AMNetCategory=Supervised method, Setting=Zero-shot2026.02 | 8.08 | 60.88 | |
| GCNType=Supervised2026.06 | 7.8 | 66.7 | |
| GCNTraining Setup=Training on Group 22026.05 | 7.63 | — | |
| GATTraining Setup=Training on Group 22026.05 | 7.37 | — | |
| GADAMType=Unsupervised2026.06 | 7.2 | 58.7 | |
| ARCType=Generalist GAD2026.06 | 7.2 | 57.4 | |
| GraphGPTMethodology=LLM-integrated2026.06 | 7.06 | — | |
| UNPromptType=Generalist GAD2026.06 | 6.2 | 60.7 | |
| BWGNNTraining Setup=Training on Group 22026.05 | 5.85 | — | |
| UNPromptCategory=Generalist method, Setting=Zero-shot2026.02 | 5.74 | 55.84 | |
| GHRNType=Supervised2026.06 | 5.7 | 61.9 | |
| GINCategory=Supervised method, Setting=Zero-shot2026.02 | 5.68 | 57.65 | |
| NRGLType=Supervised2026.06 | 5.3 | 57.3 | |
| TAMType=Unsupervised2026.06 | 5.2 | 55.7 | |
| BGNNTraining Setup=Training on Group 22026.05 | 5.12 | — | |
| AnomalyGFMCategory=Generalist method, Setting=Zero-shot2026.02 | 4.88 | 53.26 | |
| AnomalyGFMTraining Setup=Training on Group 22026.05 | 4.73 | — | |
| SAGECategory=Supervised method, Setting=Zero-shot2026.02 | 4.72 | 38.98 | |
| ANEMONETraining Setup=Training on Group 22026.05 | 4.43 | — | |
| InstructGLMMethodology=LLM-integrated2026.06 | 4.24 | — | |
| AnomalyGFMEvaluation Protocol=10-shot2026.02 | 4.13 | — | |
| AnomalyDAEType=Unsupervised2026.06 | 4 | 48.4 | |
| GATType=Supervised2026.06 | 3.5 | 39.9 | |
| DOMINANTType=Unsupervised2026.06 | 3 | 54.3 | |
| GGADType=Unsupervised2026.06 | 3 | 25.2 | |
| ANEMONE2024.10 | — | 91.89 | |
| AnomalyDAELearning Paradigm=Unsupervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 82 | |
| AnomalyGFMLearning Paradigm=Generalist, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 40.37 | |
| AnomalyGFMShot count=10-shot2026.02 | — | 46.6 | |
| AnomalyGFMTraining/Inference Setting=Supervised - Pre-Train & Few-Shot Inference, Few-Shot=10-shot2026.05 | — | 51.27 | |
| ANOMIX2024.10 | — | 94.14 | |
| ARCShot count=10-shot2026.02 | — | 82.31 | |
| ARCTraining/Inference Setting=Supervised - Pre-Train & Few-Shot Inference, Few-Shot=10-shot2026.05 | — | 90.95 | |
| BWGNNLearning Paradigm=Supervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 42.58 | |
| CoLALearning Paradigm=Unsupervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 52.56 | |
| CoLA2024.10 | — | 89.68 | |
| ComGA2024.10 | — | 91.67 | |
| DeepSAD2024.10 | — | 54.6 | |
| DOMINANT2024.10 | — | 82.51 | |
| GAD-MoRELearning Paradigm=Generalist, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 90.28 | |
| GAD-MoREShot count=0-shot2026.02 | — | 90.28 | |
| GATLearning Paradigm=Supervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 44.58 | |
| GCNLearning Paradigm=Supervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 53.83 | |
| GDN2024.10 | — | 85.48 | |
| GHRNLearning Paradigm=Supervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 54.11 | |
| GRADATE2024.10 | — | 83.13 | |
| IA-GGADLearning Paradigm=Generalist, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 91.54 | |
| LHML2024.10 | — | 80.2 | |
| MetaGAD2024.10 | — | 86.28 | |
| ProMoSTraining/Inference Setting=Unsupervised - Pre-Train Only2026.05 | — | 90.77 | |
| Semi-GNN2024.10 | — | 81.74 | |
| TAMLearning Paradigm=Unsupervised, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 46.44 | |
| UNPromptLearning Paradigm=Generalist, Evaluation Setting=Zero-shot cross-domain2026.02 | — | 59.53 |