CA
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Spatio-temporal forecasting | CA | Relative MAE0.12 | 32 | |
| Traffic Forecasting | CA | MAE (Average)17.35 | 22 | |
| Next POI Prediction | CA | ACC@120.95 | 18 | |
| Mobility Prediction | CA Foursquare Gowalla (test) | M@122.25 | 15 | |
| Next-location prediction | CA (test) | Top-1 Accuracy17.3 | 14 | |
| Energy usage prediction | CA California | MAE0.327 | 14 | |
| Next POI recommendation | CA | HR@130.38 | 13 | |
| Next POI Prediction | CA (Tail) | H@2041.28 | 13 | |
| Next POI Prediction | CA (Head) | H@2090.4 | 13 | |
| Next Point-of-Interest Recommendation | CA | HR@534.2 | 13 | |
| Next POI Recommendation | CA (test) | HR@535.84 | 13 | |
| Combinatorial Auction | CA Large-scale | Objective Value13,592.81 | 12 | |
| Next POI recommendation | CA | ND@10.1595 | 12 | |
| Combinatorial Auction | CA 2000 | Objective Value-63,197 | 10 | |
| Spatio-Temporal Time Series Forecasting | CA | MAE22.05 | 10 | |
| Federated Clustering | CA | NMI0.39 | 9 | |
| Global Clustering | CA | Purity0.436 | 9 | |
| Clustering | CA | Purity54.2 | 9 | |
| Global Clustering | CA | SC0.139 | 9 | |
| Integer Linear Programming Solving | CA | FR (%)100 | 8 | |
| Tabular Data Clustering | CA | ARI0.1862 | 8 | |
| Solving MILP instances | CA (test) | Avg Time (s)0.02 | 8 | |
| Combinatorial Auction | CA 2000 items/bids (Out-of-Distribution) | Objective Value-62,665 | 7 | |
| Combinatorial Auction | CA In-Distribution 2000 items/bids | Objective Value-63,780 | 7 | |
| 3D Object Detection | CA-1M | AP@0.25 IoU40.9 | 7 |
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