Table 2:

Partial DC between the network ${\Theta }_X$ conditioned on the network ${\Theta }_Y$, and the ImageNet class name embedding. The higher value indicates the more information.

Network ${\Theta }_X$	Network ${\Theta }_Y$	${\mathcal{R}}^2\left(X,GT\right)$	${\mathcal{R}}^2\left(Y,GT\right)$	${\mathcal{R}}^2\left(\left(X\mid Y\right),GT\right)$	${\mathcal{R}}^2\left(\left(Y\mid X\right),GT\right)$
ViT1	Resnet 182	0.042	0.025	0.035	0.007
ViT	Resnet 503	0.043	0.036	0.028	0.017
ViT	Resnet 1524	0.044	0.020	0.040	0.009
ViT	VGG 19 BN5	0.042	0.037	0.026	0.015
ViT	Densenet1216	0.043	0.026	0.035	0.007
ViT large7	Resnet 18	0.046	0.027	0.038	0.007
ViT large	Resnet 50	0.046	0.037	0.031	0.016
ViT large	Resnet 152	0.046	0.021	0.042	0.010
ViT large	ViT	0.045	0.043	0.019	0.013
ViT+Resnet 508	Resnet 18	0.044	0.024	0.037	0.005
Resnet 152	Resnet 18	0.019	0.025	0.013	0.020
Resnet 152	Resnet 50	0.021	0.037	0.003	0.030
Resnet 50	Resnet 18	0.036	0.025	0.027	0.008
Resnet 50	VGG 19 BN	0.036	0.036	0.020	0.019

Accuracy: 1.84.40%; 2. 69.76%; 3. 79.02%; 4. 82.54%; 5. 74.22%; 6. 75.57%; 7. 85.68%; 8. 84.13%