Tabular Anomaly Detection on Pima
0.7818AUC ROCLLM-DAS
Evaluation results
| Method | Links | ||
|---|---|---|---|
| LLM-DASMethod Variant=DRL2025.10 | 0.7818 | — | |
| DRL2025.10 | 0.7651 | — | |
| DRL2026.02 | 0.765 | — | |
| MCM2026.02 | 0.7639 | — | |
| MCM2025.10 | 0.7639 | — | |
| NeuTral2026.02 | 0.758 | — | |
| NPT-AD2025.10 | 0.7553 | — | |
| ICAD-LLMMethod Category=Task-Specific2025.12 | 0.7538 | — | |
| CTADBase Detector=MCM2026.02 | 0.7511 | — | |
| MCMMethod Category=Task-Specific2025.12 | 0.7486 | — | |
| KNN2026.02 | 0.743 | — | |
| REPEN2026.02 | 0.736 | — | |
| DeepSVDD2026.02 | 0.7348 | — | |
| DeepSVDD2025.10 | 0.7348 | — | |
| Best Unsupervisedsource=[9]2025.12 | 0.734 | 0.566 | |
| IForest2026.02 | 0.726 | — | |
| CTADBase Detector=DRL2026.02 | 0.7198 | — | |
| GOADMethod Category=Task-Specific2025.12 | 0.718 | — | |
| AutoEncoder2026.02 | 0.7163 | — | |
| AutoEncoder2025.10 | 0.7163 | — | |
| GOAD2026.02 | 0.715 | — | |
| OCSVM2026.02 | 0.7133 | — | |
| PCA2026.02 | 0.7133 | — | |
| OCSVM2025.10 | 0.7133 | — | |
| PCA2025.10 | 0.7133 | — | |
| RCA2026.02 | 0.712 | — | |
| PCA2026.02 | 0.708 | — | |
| ICL2026.02 | 0.706 | — | |
| LOF2025.10 | 0.6913 | — | |
| WFRDAlabeled data percentage=1%2025.12 | 0.6884 | — | |
| knn2025.12 | 0.685 | 0.58 | |
| ICAD-LLMMethod Category=Universal2025.12 | 0.6839 | — | |
| CTADBase Detector=KNN2026.02 | 0.6807 | — | |
| DTE2026.02 | 0.6788 | — | |
| DTE2025.10 | 0.6788 | — | |
| LLM-DASMethod Variant=PCA2025.10 | 0.6783 | — | |
| AnoLLM-135Mbackbone=SmolLM-135M2026.02 | 0.675 | — | |
| IForest2026.02 | 0.6737 | — | |
| IForest2025.10 | 0.6737 | — | |
| ICL2026.02 | 0.6727 | — | |
| ICL2025.10 | 0.6727 | — | |
| KNN2026.02 | 0.6723 | — | |
| KNN2025.10 | 0.6723 | — | |
| CausalTAD-135Mbackbone=SmolLM-135M2026.02 | 0.667 | — | |
| DTE2026.02 | 0.664 | — | |
| AnoLLMModel Size=135M2025.10 | 0.663 | — | |
| DeepSVDD2026.02 | 0.654 | — | |
| AnoLLMModel Size=360M2025.10 | 0.654 | — | |
| IForestMethod Category=Task-Specific2025.12 | 0.6536 | — | |
| PaLD2025.12 | 0.65 | 0.515 | |
| FRODlabeled data percentage=1%2025.12 | 0.6434 | — | |
| MFGADlabeled data percentage=1%2025.12 | 0.6391 | — | |
| NeuTraLAD2026.02 | 0.617 | — | |
| REPENlabeled data percentage=1%2025.12 | 0.6154 | — | |
| IForestlabeled data percentage=1%2025.12 | 0.6146 | — | |
| DRL2026.05 | 0.6127 | — | |
| NeuTraL ADMethod Category=Universal2025.12 | 0.6116 | — | |
| DeepSVDDlabeled data percentage=1%2025.12 | 0.6091 | — | |
| FEAWADlabeled data percentage=1%2025.12 | 0.5984 | — | |
| DAGMMMethod Category=Task-Specific2025.12 | 0.5965 | — | |
| ECODlabeled data percentage=1%2025.12 | 0.5941 | — | |
| ACRMethod Category=Universal2025.12 | 0.5938 | — | |
| ECOD2026.02 | 0.591 | — | |
| ECOD2026.02 | 0.5834 | — | |
| ECOD2025.10 | 0.5834 | — | |
| EPHAD2026.05 | 0.5809 | — | |
| UniADMethod Category=Universal2025.12 | 0.5805 | — | |
| PReNetlabeled data percentage=1%2025.12 | 0.5801 | — | |
| GOAD2026.05 | 0.5769 | — | |
| SLAD2026.02 | 0.575 | — | |
| DevNetlabeled data percentage=1%2025.12 | 0.5748 | — | |
| LOF2026.05 | 0.5662 | — | |
| Iforest2026.05 | 0.5626 | — | |
| LUNAR2026.05 | 0.5579 | — | |
| SLAD2026.05 | 0.5574 | — | |
| DeepSADlabeled data percentage=1%2025.12 | 0.5502 | — | |
| TTAD2026.05 | 0.5324 | — | |
| MCM2026.05 | 0.5251 | — | |
| NeuTraLAD2026.05 | 0.5122 | — | |
| DIF2026.05 | 0.5084 | — | |
| OCSVM2026.05 | 0.5 | — | |
| DeepSVDD2026.05 | 0.4893 | — | |
| ECOD2026.05 | 0.4893 | — | |
| ICL2026.05 | 0.4813 | — | |
| RTTAD2026.05 | 0.4798 | — | |
| GOAD2026.02 | 0.4338 | — | |
| AE2026.03 | — | 0.7122 | |
| AnoLLMModel Scale=35M2025.10 | — | 0.677 | |
| AnoLLMModel Scale=360M2025.10 | — | 0.674 | |
| AutoEncoder2025.10 | — | 0.7174 | |
| DeepSVDD2025.10 | — | 0.7165 | |
| DisentAD2026.03 | — | 0.6856 | |
| DRL2026.03 | — | 0.721 | |
| DRL2025.10 | — | 0.7449 | |
| DSVDD2026.03 | — | 0.6707 | |
| DTE2025.10 | — | 0.6798 | |
| ECOD2025.10 | — | 0.5877 | |
| ICL2025.10 | — | 0.6965 | |
| iForest2026.03 | — | 0.7194 | |
| IForest2025.10 | — | 0.6662 |