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Models/VELM

VELM

Reported on 9 benchmarks across 3 tasks · 1 paper · 9 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology8 results

Anomaly DetectiononMVTecAD
Accuracy (% )· 2025-05-05
81.4
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
Anomaly DetectiononVisA-AC
Accuracy(%)· 2025-05-05
69.6
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
Anomaly DetectiononMVTec-AC
Accuracy (% )· 2025-05-05
89.8
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
2D ClassificationonMVTecAD
Accuracy (% )· 2025-05-05
81.4
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
2D ClassificationonVisA-AC
Accuracy(%)· 2025-05-05
69.6
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
2D ClassificationonMVTec-AC
Accuracy (% )· 2025-05-05
89.8
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
Anomaly DetectiononMVTec-AC
Accuracy (% )· 2025-05-05
84
best: 89.8
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
2D ClassificationonMVTec-AC
Accuracy (% )· 2025-05-05
84
best: 89.8
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626

Computer Vision4 results

Anomaly ClassificationonMVTecAD
Accuracy (% )· 2025-05-05
81.4
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
Anomaly ClassificationonVisA-AC
Accuracy(%)· 2025-05-05
69.6
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
Anomaly ClassificationonMVTec-AC
Accuracy (% )· 2025-05-05
89.8
SOTA
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626
Anomaly ClassificationonMVTec-AC
Accuracy (% )· 2025-05-05
84
best: 89.8
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models arXiv:2505.02626