| Dataset Name | SOTA Method | Metric | Trend | ||
|---|---|---|---|---|---|
| PhiUSIIL | IFSC | Post-manipulation Accuracy88.94 | 8 | 1d ago | |
| Diabetes | IFSC | Post-manipulation Accuracy75.38 | 8 | 1d ago | |
| Adult | IFSC | Accuracy (Post-manipulation)83.22 | 8 | 1d ago | |
| Synthetic | IFSC | Post-manipulation Accuracy86.14 | 8 | 1d ago | |
| Spam | IFSC | Post-manipulation Accuracy90.62 | 8 | 1d ago | |
| German | IFSC | Post-manipulation Accuracy80.41 | 8 | 1d ago | |
| Credit | IFSC | Post-manipulation Accuracy83.96 | 8 | 1d ago | |
| Strategic Classification Non-ball Manipulations | - | - | 0 | 3mo ago | |
| Strategic Classification Ball Manipulations | - | - | 0 | 3mo ago |
