CRAFT: Concept Recursive Activation FacTorization for Explainability

CRAFT: Concept Recursive Activation FacTorization for Explainability

17 November 2022

Thibaut Boissin

David Vigouroux

Papers citing "CRAFT: Concept Recursive Activation FacTorization for Explainability"

18 / 18 papers shown

Title
Representational Similarity via Interpretable Visual Concepts Neehar Kondapaneni Oisin Mac Aodha Pietro Perona DRL 74 0 0 19 Mar 2025
Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models Itay Benou Tammy Riklin-Raviv 59 0 0 27 Feb 2025
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment Harrish Thasarathan Julian Forsyth Thomas Fel M. Kowal Konstantinos G. Derpanis 97 7 0 06 Feb 2025
COMIX: Compositional Explanations using Prototypes S. Sivaprasad D. Kangin Plamen Angelov Mario Fritz 61 0 0 10 Jan 2025
Explaining the Impact of Training on Vision Models via Activation Clustering Ahcène Boubekki Samuel G. Fadel Sebastian Mair 89 0 0 29 Nov 2024
GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers Éloi Zablocki Valentin Gerard Amaia Cardiel Eric Gaussier Matthieu Cord Eduardo Valle 69 0 0 23 Nov 2024
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 51 1 0 01 Jul 2024
Generating Counterfactual Trajectories with Latent Diffusion Models for Concept Discovery Payal Varshney Adriano Lucieri Christoph Balada Andreas Dengel Sheraz Ahmed MedIm DiffM 36 3 0 16 Apr 2024
Natural Example-Based Explainability: a Survey Antonin Poché Lucas Hervier M. Bakkay XAI 13 11 0 05 Sep 2023
Uncovering Unique Concept Vectors through Latent Space Decomposition Mara Graziani Laura Mahony An-phi Nguyen Henning Muller Vincent Andrearczyk 31 4 0 13 Jul 2023
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex Drew Linsley I. F. Rodriguez Thomas Fel Michael Arcaro Saloni Sharma Margaret Livingstone Thomas Serre 22 18 0 06 Jun 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 43 17 0 30 Dec 2022
Toy Models of Superposition Nelson Elhage Tristan Hume Catherine Olsson Nicholas Schiefer T. Henighan ... Sam McCandlish Jared Kaplan Dario Amodei Martin Wattenberg C. Olah AAML MILM 120 314 0 21 Sep 2022
Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence Frederik Pahde Maximilian Dreyer Leander Weber Moritz Weckbecker Christopher J. Anders Thomas Wiegand Wojciech Samek Sebastian Lapuschkin 55 7 0 07 Feb 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 58 112 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 112 57 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 241 417 0 15 Oct 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017