German
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | German | Accuracy79.4 | 58 | |
| Node Classification | German (test) | F1 Score80.54 | 22 | |
| Algorithmic Recourse | German (10-fold cross-validation) | Recourse Cost (MPS)0.02 | 21 | |
| Classification | German | Delta DP-0.1023 | 20 | |
| Graph Multiple Sensitive Attribute Inference Attack | German | AA72.62 | 19 | |
| AUC Maximization | german | AUC0.763 | 19 | |
| Classification | German (test) | Error Rate23.12 | 16 | |
| Classification | German | Acc72.5 | 15 | |
| Conversational XAI | german | Faithfulness80 | 12 | |
| Binary Classification | German | Accuracy73.5 | 12 | |
| Unsupervised Constituency Parsing | German SPMRL (test) | S-F149.5 | 11 | |
| Time Series Forecasting | German | Improvement Rate71.9 | 9 | |
| Classification | german UCI | Accuracy70 | 9 | |
| Link Prediction | German | Micro-F190.5 | 9 | |
| Named Entity Recognition | German (test) | F1 Score78.76 | 9 | |
| Classification | German | Individual Fairness Gap0.142 | 8 | |
| Strategic Classification | German | Post-manipulation Accuracy80.41 | 8 | |
| Classification | German 80% (train) | VI60 | 8 | |
| Classification | German UCI (test 20%) | VI10.52 | 8 | |
| Node Classification | German | H Metric (Acc, DP, EO)0.0002 | 8 | |
| Node Classification | German | Training Time (s)7 | 8 | |
| Binary Classification | German | Mean F1 Score65.5664 | 8 | |
| Binary Classification | german LIBSVM (test) | AUC0.799 | 7 | |
| Classification | german dataset | ACC79.3 | 6 | |
| Multilingual Language Understanding | German | Average Performance55.7 | 6 |
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