Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis

15 February 2022

Papers citing "Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis"

32 / 32 papers shown

Title
Towards Robust and Generalizable Gerchberg Saxton based Physics Inspired Neural Networks for Computer Generated Holography: A Sensitivity Analysis Framework Ankit Amrutkar Björn Kampa Volkmar Schulz Johannes Stegmaier Markus Rothermel Dorit Merhof 16 0 0 30 Apr 2025
Tokenize Image Patches: Global Context Fusion for Effective Haze Removal in Large Images Jiuchen Chen Xinyu Yan Qizhi Xu Kaiqi Li VLM 27 0 0 13 Apr 2025
Escaping Plato's Cave: Robust Conceptual Reasoning through Interpretable 3D Neural Object Volumes Nhi Pham Bernt Schiele Adam Kortylewski Jonas Fischer 56 0 0 17 Mar 2025
Exploring Channel Distinguishability in Local Neighborhoods of the Model Space in Quantum Neural Networks Sabrina Herbst S. S. Cranganore Vincenzo De Maio Ivona Brandić 45 0 0 17 Feb 2025
OMENN: One Matrix to Explain Neural Networks Adam Wróbel Mikołaj Janusz Bartosz Zieliñski Dawid Rymarczyk FAtt AAML 75 0 0 03 Dec 2024
SPES: Spectrogram Perturbation for Explainable Speech-to-Text Generation Dennis Fucci Marco Gaido Beatrice Savoldi Matteo Negri Mauro Cettolo L. Bentivogli 54 1 0 03 Nov 2024
Explainable Image Recognition via Enhanced Slot-attention Based Classifier Bowen Wang Liangzhi Li Jiahao Zhang Yuta Nakashima Hajime Nagahara OCL 44 0 0 08 Jul 2024
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness Kejia Zhang Juanjuan Weng Yuanzheng Cai Zhiming Luo Shaozi Li AAML 59 0 0 04 Jul 2024
A Study of Nationality Bias in Names and Perplexity using Off-the-Shelf Affect-related Tweet Classifiers Valentin Barriere Sebastian Cifuentes 28 0 0 01 Jul 2024
Understanding Inhibition Through Maximally Tense Images Chris Hamblin Srijani Saha Talia Konkle George Alvarez FAtt 32 0 0 08 Jun 2024
Local vs. Global Interpretability: A Computational Complexity Perspective Shahaf Bassan Guy Amir Guy Katz 35 6 0 05 Jun 2024
Tensor Polynomial Additive Model Yang Chen Ce Zhu Jiani Liu Yipeng Liu TPM 25 0 0 05 Jun 2024
Feature Accentuation: Revealing 'What' Features Respond to in Natural Images Christopher Hamblin Thomas Fel Srijani Saha Talia Konkle George A. Alvarez FAtt 21 3 0 15 Feb 2024
Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks Stefan Blücher Johanna Vielhaben Nils Strodthoff AAML 61 20 0 12 Jan 2024
Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning Tom Nuno Wolf Fabian Bongratz Anne-Marie Rickmann Sebastian Polsterl Christian Wachinger AAML FAtt 40 6 0 15 Dec 2023
Deep Natural Language Feature Learning for Interpretable Prediction Felipe Urrutia Cristian Buc Valentin Barriere 26 1 0 09 Nov 2023
Natural Example-Based Explainability: a Survey Antonin Poché Lucas Hervier M. Bakkay XAI 26 11 0 05 Sep 2023
Formally Explaining Neural Networks within Reactive Systems Shahaf Bassan Guy Amir Davide Corsi Idan Refaeli Guy Katz AAML 25 15 0 31 Jul 2023
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization Thomas Fel Thibaut Boissin Victor Boutin Agustin Picard Paul Novello ... Drew Linsley Tom Rousseau Rémi Cadène Laurent Gardes Thomas Serre FAtt 16 18 0 11 Jun 2023
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation Thomas Fel Victor Boutin Mazda Moayeri Rémi Cadène Louis Bethune Léo Andéol Mathieu Chalvidal Thomas Serre FAtt 16 49 0 11 Jun 2023
Assessment of the Reliablity of a Model's Decision by Generalizing Attribution to the Wavelet Domain Gabriel Kasmi L. Dubus Yves-Marie Saint Drenan Philippe Blanc FAtt 16 3 0 24 May 2023
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines? Victor Boutin Thomas Fel Lakshya Singhal Rishav Mukherji Akash Nagaraj Julien Colin Thomas Serre DiffM 22 6 0 27 Jan 2023
CRAFT: Concept Recursive Activation FacTorization for Explainability Thomas Fel Agustin Picard Louis Bethune Thibaut Boissin David Vigouroux Julien Colin Rémi Cadène Thomas Serre 19 102 0 17 Nov 2022
Harmonizing the object recognition strategies of deep neural networks with humans Thomas Fel Ivan Felipe Drew Linsley Thomas Serre 30 71 0 08 Nov 2022
Towards Formal XAI: Formally Approximate Minimal Explanations of Neural Networks Shahaf Bassan Guy Katz FAtt AAML 21 22 0 25 Oct 2022
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective M. Serrurier Franck Mamalet Thomas Fel Louis Bethune Thibaut Boissin AAML FAtt 26 4 0 14 Jun 2022
Xplique: A Deep Learning Explainability Toolbox Thomas Fel Lucas Hervier David Vigouroux Antonin Poché Justin Plakoo ... Agustin Picard C. Nicodeme Laurent Gardes G. Flandin Thomas Serre 11 30 0 09 Jun 2022
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods Julien Colin Thomas Fel Rémi Cadène Thomas Serre 25 101 0 06 Dec 2021
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
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 242 3,681 0 28 Feb 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 226 1,835 0 03 Feb 2017