Uncertainty Estimation on Events
61.77AUROCLayer Top-m Prob.
Evaluation results
| Method | Links | |
|---|---|---|
| Layer Top-m Prob.Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Layer Top-m Prob.2026.06 | 61.77 | |
| Internal VarianceProbe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Internal Variance2026.06 | 59.28 | |
| Linear (#256)Probe Type=Baseline, Probe Architecture=Linear, Number of Training Samples=256, Feature Representation=Embedding (last)2026.06 | 57.3 | |
| Linear (#128)Probe Type=Baseline, Probe Architecture=Linear, Number of Training Samples=128, Feature Representation=Embedding (last)2026.06 | 57.22 | |
| Ensemble (task)Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Ensemble of probes on pooled data2026.06 | 56.79 | |
| Lookback RatioProbe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Lookback Ratio2026.06 | 56.6 | |
| Ensemble (probe)Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Ensemble of three Internal variance probes2026.06 | 55 | |
| MLP (#128)Probe Type=Baseline, Probe Architecture=MLP, Number of Training Samples=128, Feature Representation=Embedding (last)2026.06 | 54.4 | |
| Linear (#64)Probe Type=Baseline, Probe Architecture=Linear, Number of Training Samples=64, Feature Representation=Embedding (last)2026.06 | 53.75 | |
| Embedding (last)Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Embedding (last)2026.06 | 50.93 |