Scenario
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Perceived Risk Prediction | Scenario MB | RMSE0.2391 | 81 | |
| Binary Classification | Scenario 3 (val) | Delta TCC253 | 24 | |
| Binary Classification | Scenario 2 (val) | Delta TCC591 | 24 | |
| Binary Classification | Scenario 1 (val) | Delta TCC0 | 24 | |
| Regression | Scenario IS2 | Size0 | 24 | |
| Classification | Scenario IS1 | Model Size0 | 24 | |
| Change point localization | Scenario 5 | Mismatch Proportion (K!=K)0.055 | 20 | |
| Change point localization | Scenario 3 | Error Proportion (K_hat != K)70.5 | 20 | |
| Quantile Regression | Scenario 3 n=10000 | MSE (tau=0.05)0.6307 | 16 | |
| Quantile Regression | Scenario 3 n=5000 | MSE (τ=0.05)0.8839 | 16 | |
| Quantile Regression | Scenario 3 n=1000 | MSE (τ=0.05)1.9425 | 16 | |
| Quantile Regression | Scenario 2 n=10000 | MSE (τ=0.05)0.1008 | 16 | |
| Quantile Regression | Scenario 2 (n=5000) | MSE (τ=0.05)0.143 | 16 | |
| Quantile Regression | Scenario 2 n=1000 | MSE (τ=0.05)0.4515 | 16 | |
| Quantile Regression | Scenario 1 n=10000 | MSE (τ=0.05)0.0618 | 16 | |
| Quantile Regression | Scenario 1 (n=5000) | MSE (Quantile 0.05)0.0996 | 16 | |
| Policy Value Estimation | Scenario 4 | Policy Value Mean6.714 | 15 | |
| Policy Value Estimation | Scenario 3 | Policy Value (mean)1.879 | 15 | |
| Individualized Treatment Rule Estimation | Scenario 2 | Policy Value (PV)1.095 | 15 | |
| Individualized Treatment Rule Estimation | Scenario 1 | Policy Value (PV)1.017 | 15 | |
| Multi-agent trajectory planning | 10 agent scenario (ground truth goals) | Trajectory Success Rate2.31 | 12 | |
| Change point localization | Scenario 1 T=300 | Prop. K_hat != K1 | 10 | |
| Change point localization | Scenario 1 T=150 | Error Proportion0 | 10 | |
| Causal Action Execution | Scenario S4 | Success Rate100 | 9 | |
| Single-Step Action Execution | Scenario S2 | Success Rate100 | 9 |
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