Image Classification on ImageNet-1K (val) (Efficiency Deltas)
0Top-1 Accuracy Delta (pp)GTP-15.3
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| GTP-15.3Backbone=DeiT-B/162025.09 | 0 | 13.07 | 0 | |
| BALF-P-0.8Backbone=DeiT-B/162025.09 | 0.17 | 19.36 | 19.94 | |
| BALF-F-0.8Backbone=DeiT-B/162025.09 | 0.19 | 19.22 | 19.79 | |
| BALF-P-0.9Backbone=MobileNetV22025.09 | 0.23 | 0.12 | 10.69 | |
| DC-ViTBackbone=DeiT-B/162025.09 | 0.54 | 16.6 | — | |
| BALF-P-0.8Backbone=MobileNetV22025.09 | 0.61 | 0.23 | 19.8 | |
| BALF-P-0.8Backbone=ResNet-502025.09 | 1.11 | 9.03 | 21.9 | |
| BALF-F-0.7Backbone=DeiT-B/162025.09 | 1.25 | 28.78 | 29.64 | |
| BALF-P-0.7Backbone=DeiT-B/162025.09 | 1.34 | 29.04 | 29.91 | |
| IFMBackbone=ResNet-50, Setting=Row 12025.09 | 1.46 | — | 5.65 | |
| BALF-P-0.8Backbone=ResNet-18, Objective=Parameter count objective2025.09 | 1.69 | 6.77 | 22.28 | |
| BALF-F-0.8Backbone=ResNet-502025.09 | 1.69 | 20.03 | 9.73 | |
| CP-ALS-SBackbone=ResNet-18, Setting=High parameters2025.09 | 1.91 | — | 51.69 | |
| BALF-P-0.7Backbone=ResNet-502025.09 | 1.97 | 13.6 | 29.95 | |
| PRACTISEBackbone=DeiT-B/162025.09 | 2.5 | 16.6 | — | |
| T-ALS-SBackbone=ResNet-50, Setting=Row 12025.09 | 2.57 | — | 27.54 | |
| T-ALS-SBackbone=ResNet-18, Setting=High parameters2025.09 | 3 | — | 28.57 | |
| ITVSPBackbone=ResNet-50, Setting=Row 12025.09 | 3.02 | — | 4.76 | |
| BALF-P-0.7Backbone=ResNet-18, Objective=Parameter count objective2025.09 | 3.2 | 9.13 | 29.99 | |
| CP-ALSBackbone=ResNet-18, Setting=High parameters2025.09 | 3.22 | — | 51.69 | |
| BALF-F-0.7Backbone=ResNet-502025.09 | 3.5 | 30.01 | 21.66 | |
| GTP-8.8Backbone=DeiT-B/162025.09 | 3.5 | 50 | 0 | |
| BALF-F-0.6Backbone=DeiT-B/162025.09 | 4.1 | 38.37 | 39.52 | |
| BALF-P-0.6Backbone=DeiT-B/162025.09 | 4.31 | 38.71 | 39.87 | |
| L2+RESTBackbone=MobileNetV2, Setting=Low parameters2025.09 | 4.42 | — | 5 | |
| T-ALSBackbone=ResNet-50, Setting=Row 12025.09 | 4.49 | — | 27.54 | |
| BALF-F-0.97Backbone=MobileNetV22025.09 | 4.89 | 2.51 | 1.55 | |
| BALF-F-0.8Backbone=ResNet-18, Objective=FLOP objective2025.09 | 5.49 | 20.01 | 16.74 | |
| DFPCBackbone=ResNet-50, Setting=Row 12025.09 | 5.78 | — | 5.66 | |
| BALF-P-0.75Backbone=MobileNetV22025.09 | 6.17 | 1.13 | 24.78 | |
| T-ALS-SBackbone=ResNet-18, Setting=Low parameters2025.09 | 6.5 | — | 43.5 | |
| CP-ALS-SBackbone=ResNet-18, Setting=Low parameters2025.09 | 6.7 | — | 69.23 | |
| T-ALS-SBackbone=ResNet-50, Setting=Row 22025.09 | 6.9 | — | 33.33 | |
| BALF-P-0.6Backbone=ResNet-18, Objective=Parameter count objective2025.09 | 7 | 13.26 | 40.01 | |
| BALF-P-0.5Backbone=ResNet-502025.09 | 7.79 | 28.17 | 50.06 | |
| CP-ALSBackbone=ResNet-18, Setting=Low parameters2025.09 | 8.03 | — | 60.47 | |
| BALF-F-0.7Backbone=ResNet-18, Objective=FLOP objective2025.09 | 8.5 | 30.71 | 28.68 | |
| ITVSPBackbone=ResNet-50, Setting=Row 22025.09 | 10.21 | — | 9.98 | |
| IFMBackbone=ResNet-50, Setting=Row 22025.09 | 10.45 | — | 20.42 | |
| T-ALSBackbone=ResNet-18, Setting=High parameters2025.09 | 10.9 | — | 28.57 | |
| SVD-NASBackbone=MobileNetV22025.09 | 12.54 | 15.09 | 9 | |
| SVD-NASBackbone=ResNet-182025.09 | 13.35 | 58.6 | 68.05 | |
| DFPCBackbone=ResNet-50, Setting=Row 22025.09 | 13.88 | — | 10.92 | |
| BALF-F-0.5Backbone=ResNet-502025.09 | 13.96 | 50.03 | 43.84 | |
| BALF-F-0.6Backbone=ResNet-18, Objective=FLOP objective2025.09 | 15.25 | 41.18 | 39.45 | |
| ALDSBackbone=MobileNetV22025.09 | 16.95 | 2.62 | 37.61 | |
| LR-S2Backbone=MobileNetV22025.09 | 17.46 | 3.81 | 6.24 | |
| T-ALSBackbone=ResNet-18, Setting=Low parameters2025.09 | 17.6 | — | 33.33 | |
| L2+RESTBackbone=MobileNetV2, Setting=High parameters2025.09 | 18.47 | — | 10 | |
| ALDSBackbone=ResNet-182025.09 | 18.7 | 42.31 | 65.14 | |
| T-ALSBackbone=ResNet-50, Setting=Row 22025.09 | 20.14 | — | 33.33 | |
| BALF-P-0.7Backbone=MobileNetV22025.09 | 28.08 | 2.07 | 29.72 |