Unverified50% confidenceBenchmarkExact time
A linear probe predicting pose failure on VGGT's frozen features achieved an ROC-AUC of 93.5% on unseen categories.
1
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50%
Confidence
Medium-term (~90 days)
Relevance
10/27/2026
First Seen
Valid until: 1/25/2027
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Related Claims
UnverifiedUsing the behavioral features of each state for failure prediction, the AUROC on the held-out set reaches as high as 0.94.71% similarUnverifiedThe ROC curve uses the false positive rate FPR = FP / (FP + TN) as the horizontal axis; when the number of negative samples is extremely large, the FPR will appear very low.67% similarUnverifiedOn the validation set, GAM achieved an AUC of 0.89, a sensitivity of 0.83, and a specificity of 0.82.66% similarUnverifiedReachNT's urgency model achieves a ROC-AUC of 0.84 on unseen phrasing, and as part of an overall system that includes human review it catches 99.3% of dangerous work orders.66% similarUnverifiedOn synthetic data with 10,000 samples, a 1% positive rate, and 495 negatives scoring 0.90 while the positives score 0.80 and 0.60 respectively, computing with a 0.5 threshold gives: ROC-AUC=0.9500, Average Precision=0.1449, precision=0.1681, recall=1.0000, accuracy=0.9505, TP=100, FP=495, TN=9405, FN=0.66% similar
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