118 citations · 219 across the 22 of their papers we have counts for
4 papers · 1 filter
Model Guidance via Explanations Turns Image Classifiers into Segmentation Models
Xiaoyan Yu, Jannik Franzen, Wojciech Samek +2
Heatmaps generated on inputs of image classification networks via explainable AI methods like Grad-CAM and LRP have been observed to resemble segmentations of input images in many…
CoSy: Evaluating Textual Explanations of Neurons
Laura Kopf, Philine Lou Bommer, Anna Hedström +3
A crucial aspect of understanding the complex nature of Deep Neural Networks (DNNs) is the ability to explain learned concepts within their latent representations. While methods ex…
Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test
Anna Hedström, Leander Weber, Sebastian Lapuschkin +1
The Model Parameter Randomisation Test (MPRT) is widely acknowledged in the eXplainable Artificial Intelligence (XAI) community for its well-motivated evaluative principle: that th…
Manipulating Feature Visualizations with Gradient Slingshots
Dilyara Bareeva, Marina M. -C. Höhne, Alexander Warnecke +5
Feature Visualization (FV) is a widely used technique for interpreting concepts learned by Deep Neural Networks (DNNs), which synthesizes input patterns that maximally activate a g…