Uncertainty Estimation on Inventions
72.96AUROCLayer 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 | 72.96 | |
| Ensemble (task)Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Ensemble of probes on pooled data2026.06 | 70.23 | |
| Internal VarianceProbe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Internal Variance2026.06 | 69.9 | |
| Ensemble (probe)Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Ensemble of three Internal variance probes2026.06 | 68.08 | |
| Linear (#256)Probe Type=Baseline, Probe Architecture=Linear, Number of Training Samples=256, Feature Representation=Embedding (last)2026.06 | 61.63 | |
| Linear (#128)Probe Type=Baseline, Probe Architecture=Linear, Number of Training Samples=128, Feature Representation=Embedding (last)2026.06 | 60.81 | |
| Linear (#64)Probe Type=Baseline, Probe Architecture=Linear, Number of Training Samples=64, Feature Representation=Embedding (last)2026.06 | 59.56 | |
| Embedding (last)Probe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Embedding (last)2026.06 | 59.29 | |
| MLP (#128)Probe Type=Baseline, Probe Architecture=MLP, Number of Training Samples=128, Feature Representation=Embedding (last)2026.06 | 58.03 | |
| Lookback RatioProbe Type=Pretrained, Probe Architecture=Linear, Feature Representation=Lookback Ratio2026.06 | 57.08 |