Data for "Beyond Overconfidence: Model Advances and Domain Shifts Redefine Calibration in Neural Networks"

The repository contains model outputs from our study on neural network calibration across various architectures and domains. Available Datasets: ImageNet ImageNet-V2 ImageNet-A Breast Ultrasound Retinal OCT Pneumonia Derma (HAM10000) Derma-C Each .safetensor file includes: Model logits and ground truth labels for the validation set (for the distribution-shifted datasets) Model logits and ground truth labels for the test set File Naming Convention: [model_name]_output.safetensor, where model_name is the string identifier from the timm library. Available Models: ConvNeXt EVA BEiT ViT Swin Transformer ResNet Note: Due to size constraints, we have not been able to upload the ImageNet-C model outputs. However, these outputs can be made available upon request.