Tabular Learning on TabReD
2.3RankMaskTab(Base)
Evaluation results
| Method | Links | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| MaskTab(Base)2026.05 | 2.3 | — | — | — | — | — | — | — | — | |
| TabMadaptation=Adaptive, modeling_technique=Temporal Modulation2025.12 | 3.5 | 96.41 | 63.18 | 84.57 | 0.2285 | 0.4773 | 0.5491 | 0.161 | 1.4794 | |
| CatBoostadaptation=Static, type=Classical2025.12 | 4.375 | 96.39 | 62.42 | 86.2 | 0.2292 | 0.4792 | 0.5495 | 0.161 | 1.4654 | |
| XGBoost2026.05 | 4.4 | — | — | — | — | — | — | — | — | |
| MLP-PLR2026.05 | 4.4 | — | — | — | — | — | — | — | — | |
| TabMadaptation=Adaptive, modeling_technique=Temporal Embedding [6]2025.12 | 5.125 | 96.29 | 62.71 | 83.63 | 0.2321 | 0.4791 | 0.5488 | 0.1609 | 1.4812 | |
| LightGBM2026.05 | 5.5 | — | — | — | — | — | — | — | — | |
| CatBoost2026.05 | 5.6 | — | — | — | — | — | — | — | — | |
| XGBoostadaptation=Static, type=Classical2025.12 | 6.375 | 96.25 | 61.99 | 86.44 | 0.2262 | 0.4792 | 0.552 | 0.161 | 1.47 | |
| FT-Transformer2026.05 | 6.4 | — | — | — | — | — | — | — | — | |
| TabMadaptation=Static, type=Deep2025.12 | 7.25 | 96.4 | 63.25 | 82.9 | 0.2306 | 0.4813 | 0.55 | 0.1612 | 1.4887 | |
| LightGBMadaptation=Static, type=Classical2025.12 | 7.375 | 96.31 | 61.64 | 85.99 | 0.226 | 0.4877 | 0.55 | 0.1612 | 1.4654 | |
| ModernNCAadaptation=Adaptive, modeling_technique=Temporal Embedding [6]2025.12 | 7.625 | 96.2 | 63.56 | 83.16 | 0.2255 | 0.4791 | 0.5535 | 0.1617 | 1.4903 | |
| ResNet2026.05 | 8 | — | — | — | — | — | — | — | — | |
| TabR2026.05 | 8.6 | — | — | — | — | — | — | — | — | |
| CM22026.05 | 9 | — | — | — | — | — | — | — | — | |
| ModernNCAadaptation=Static, type=Deep2025.12 | 9.125 | 96.1 | 63.41 | 83.78 | 0.2325 | 0.4804 | 0.552 | 0.1619 | 1.4857 | |
| MLP-PLRadaptation=Adaptive, modeling_technique=Temporal Modulation2025.12 | 10 | 95.91 | 61.33 | 81.9 | 0.234 | 0.478 | 0.5474 | 0.1616 | 1.5134 | |
| TabRadaptation=Adaptive, modeling_technique=Temporal Embedding [6]2025.12 | 10.125 | 96.06 | 62.33 | 84.26 | 0.2392 | 0.4827 | 0.5497 | 0.1627 | 1.462 | |
| SNN2026.05 | 10.5 | — | — | — | — | — | — | — | — | |
| TabNet2026.05 | 10.5 | — | — | — | — | — | — | — | — | |
| MLP-PLRadaptation=Static, type=Deep2025.12 | 10.875 | 95.96 | 61.85 | 81.66 | 0.2361 | 0.4799 | 0.5481 | 0.1616 | 1.5235 | |
| MLPadaptation=Adaptive, modeling_technique=Temporal Modulation2025.12 | 11 | 95.93 | 62.3 | 55.32 | 0.2345 | 0.4782 | 0.5502 | 0.1616 | 1.5179 | |
| Trompt2026.05 | 11 | — | — | — | — | — | — | — | — | |
| FT-Tadaptation=Adaptive, modeling_technique=Temporal Embedding [6]2025.12 | 11.125 | 96.08 | 62.11 | 55.63 | 0.2363 | 0.4778 | 0.5503 | 0.1622 | 1.5118 | |
| MLP-PLRadaptation=Adaptive, modeling_technique=Temporal Embedding [6]2025.12 | 11.25 | 96.07 | 61.1 | 81.58 | 0.2338 | 0.4803 | 0.5494 | 0.1617 | 1.5133 | |
| DCNv22026.05 | 11.4 | — | — | — | — | — | — | — | — | |
| TabRadaptation=Static, type=Deep2025.12 | 13.75 | 96.05 | 61.48 | 83.42 | 0.237 | 0.4883 | 0.555 | 0.1623 | 1.4732 | |
| MLPadaptation=Adaptive, modeling_technique=Temporal Embedding [6]2025.12 | 14.375 | 94.71 | 62.52 | 55.19 | 0.2431 | 0.4801 | 0.5518 | 0.1621 | 1.5319 | |
| FT-Tadaptation=Static, type=Deep2025.12 | 15.125 | 95.91 | 61.59 | 57.46 | 0.2438 | 0.4807 | 0.5503 | 0.1623 | 1.5146 | |
| MLPadaptation=Static, type=Deep2025.12 | 16 | 93.6 | 62.2 | 55.08 | 0.2641 | 0.4821 | 0.5515 | 0.1619 | 1.5362 | |
| RandomForestadaptation=Static, type=Classical2025.12 | 17.375 | 95.8 | 60.68 | 81.71 | 0.24 | 0.4841 | 0.5588 | 0.1647 | 1.5845 | |
| Linearadaptation=Static, type=Classical2025.12 | 18.25 | 93.88 | 59.44 | 82.31 | 0.2435 | 0.4864 | 0.5596 | 0.168 | 1.7464 |