Deep learning-based interpretation Methods that are dependent on deep learning, but not specifically transformersbased, usually depend on the calculation of the gradients for their interpretation. The most straightforward way is to use the basic full gradients over the entire model. Integrated gradients (IG) contrasts gradients of a prediction iteratively with the gradients of a background sample by integrating over the differences between input parameters of the sample x and the input parameters of the empty background x (Eq. 9).