Image Classification on CIFAR-10 (test) (Natural and Auto Attack Accuracy Evaluation) benchmark leaderboard · SOTA2 Research

Image Classification on CIFAR-10 (test) (Natural and Auto Attack Accuracy Evaluation)

84.72Natural AccuracyPGD-2

Evaluation Results

Method	Links
PGD-22025.12		84.72	42.92
V-FGSM2025.12		84.26	0
R-FGSM2025.12		84.12	42.88
R-LAP2025.12		83.81	43.14
MultiGrad2025.12		83.72	0
ZeroGrad2025.12		82.54	0
Grad Align2025.12		82.35	44.76
MultiGrad2025.12		81.83	44.19
ZeroGrad2025.12		81.71	43.28
MultiGrad2025.12		81.59	0
PGD-102025.12		80.91	46.37
N-LAP2025.12		80.76	44.97
N-FGSM2025.12		80.4	44.21
V-FGSM2025.12		79.92	0
R-FGSM2025.12		79.49	0
PGD-22025.12		79.13	28.3
V-LAP2025.12		79.09	41.24
ZeroGrad2025.12		77.75	22.56
AT Free2025.12		76.52	40.13
Grad Align2025.12		74.8	29.88
R-LAP2025.12		74.1	26.04
R-FGSM2025.12		73.67	0
MultiGrad2025.12		73.5	0
V-FGSM2025.12		72.72	0
PGD-22025.12		72.5	17.89
PGD-102025.12		72.03	33.13
N-LAP2025.12		71.91	30.6
N-FGSM2025.12		71.44	30.25
ZeroGrad2025.12		68.95	0
AT Free2025.12		68.28	27.65
PGD-102025.12		67.61	21.98
V-LAP2025.12		66.2	24.07
V-FGSM2025.12		65.52	0
R-LAP2025.12		64.83	15.69
N-LAP2025.12		63.73	19.55
N-FGSM2025.12		62.91	18.58
Grad Align2025.12		61.1	19.07
AT Free2025.12		59.25	0
V-LAP2025.12		56.02	15.17
AT Free2025.12		55.91	0
PGD-22025.12		48.99	3.76
PGD-102025.12		35.28	10.88
R-FGSM2025.12		33.31	0
N-LAP2025.12		29.19	8.85
N-FGSM2025.12		27.66	0
R-LAP2025.12		27.49	8.04
Grad Align2025.12		24.15	6.71
V-LAP2025.12		17.76	7.12