This is the official repository for Taming False Positives in Out-of-Distribution Detection with Human Feedback.
Install the environment by conda env create -f environment.yml.
You can run any experiments by setting the correct configuration script. configuration scripts are located at configs. For example, to run the cifar10 experiment with change detection:
bash run.sh cifar10_change.yaml
Make sure that the configs/cifar10_change.yaml exists in the directory (which we have already provided). The log and results are stored in the output folder, and the plots are stored in the plot folder.
configs: this folder contains the parameters configuration of the experiments, including the mode, the importance sampling rate, the window size, etc.
score: we have included all the OOD scores we used in the paper, including CIFAR-10, CIFAR-100, MNIST, SVHN, Texture, TinyImageNet, and Places365 datasets
output: by default, the result would be stored as .pkl files here.
plot: by default, the plots of the result would be stored here.