This project aims to reproduce the findings of the paper "LICO: Explainable Models with Language-Image Consistency". LICO integrates linguistic prompts with visual features to enhance interpretability in image classification, using optimal transport theory for improved feature correlation.
the notebooks are can be run in colab for a complete overview.
The rest of the files can be run together to train the models properly.