Title
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment Harrish Thasarathan Julian Forsyth Thomas Fel M. Kowal Konstantinos G. Derpanis 111 7 0 06 Feb 2025
GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers Éloi Zablocki Valentin Gerard Amaia Cardiel Eric Gaussier Matthieu Cord Eduardo Valle 81 0 0 23 Nov 2024
Flow AM: Generating Point Cloud Global Explanations by Latent Alignment Hanxiao Tan 41 1 0 29 Apr 2024
Labeling Neural Representations with Inverse Recognition Kirill Bykov Laura Kopf Shinichi Nakajima Marius Kloft Marina M.-C. Höhne BDL 29 15 0 22 Nov 2023
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations Amin Ghiasi Hamid Kazemi Steven Reich Chen Zhu Micah Goldblum Tom Goldstein 48 15 0 31 Jan 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 66 114 0 06 Dec 2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis Thomas Fel Rémi Cadène Mathieu Chalvidal Matthieu Cord David Vigouroux Thomas Serre MLAU FAtt AAML 114 58 0 07 Nov 2021
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI Alon Jacovi Ana Marasović Tim Miller Yoav Goldberg 255 426 0 15 Oct 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,572 0 17 Apr 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,690 0 28 Feb 2017
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 206 14,376 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 312 36,381 0 25 Aug 2016