This repository from Google PAIR provides implementations of multiple saliency and attribution techniques for deep learning models, particularly convolutional neural networks. It enables visualization of which input features most influence model predictions, serving the Explainable AI domain. The library includes methods like Guided Integrated Gradients, XRAI, SmoothGrad, and Blur IG, along with the PIC metric for evaluating saliency quality without human annotation.