A Benchmark for Interpretability Methods in Deep Neural Networks

28 June 2018

Sara Hooker

D. Erhan

Pieter-Jan Kindermans

Papers citing "A Benchmark for Interpretability Methods in Deep Neural Networks"

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Title
From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection Moritz Vandenhirtz Julia E. Vogt 29 0 0 09 May 2025
PhysNav-DG: A Novel Adaptive Framework for Robust VLM-Sensor Fusion in Navigation Applications Trisanth Srinivasan Santosh Patapati 34 0 0 03 May 2025
Axiomatic Explainer Globalness via Optimal Transport Davin Hill Josh Bone A. Masoomi Max Torop Jennifer Dy 93 1 0 13 Mar 2025
FW-Shapley: Real-time Estimation of Weighted Shapley Values Pranoy Panda Siddharth Tandon V. Balasubramanian TDI 65 0 0 09 Mar 2025
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability Zhiyu Zhu Zhibo Jin Jiayu Zhang Nan Yang Jiahao Huang Jianlong Zhou Fang Chen 39 0 0 16 Feb 2025
A Robust Adversarial Ensemble with Causal (Feature Interaction) Interpretations for Image Classification Chunheng Zhao P. Pisu G. Comert N. Begashaw Varghese Vaidyan Nina Christine Hubig AAML 24 0 0 31 Dec 2024
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI Xu Zheng Farhad Shirani Zhuomin Chen Chaohao Lin Wei Cheng Wenbo Guo Dongsheng Luo AAML 28 0 0 03 Oct 2024
Explainable AI needs formal notions of explanation correctness Stefan Haufe Rick Wilming Benedict Clark Rustam Zhumagambetov Danny Panknin Ahcène Boubekki XAI 26 0 0 22 Sep 2024
Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data Suryansh Vidya Kush Gupta Amir Aly Andy Wills Emmanuel Ifeachor Rohit Shankar 26 1 0 19 Sep 2024
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Models Sepehr Kamahi Yadollah Yaghoobzadeh 32 0 0 21 Aug 2024
On the Evaluation Consistency of Attribution-based Explanations Jiarui Duan Haoling Li Haofei Zhang Hao Jiang Mengqi Xue Li Sun Mingli Song Jie Song XAI 46 0 0 28 Jul 2024
Benchmarking the Attribution Quality of Vision Models Robin Hesse Simone Schaub-Meyer Stefan Roth FAtt 29 3 0 16 Jul 2024
Inpainting the Gaps: A Novel Framework for Evaluating Explanation Methods in Vision Transformers Lokesh Badisa Sumohana S. Channappayya 40 0 0 17 Jun 2024
Influence based explainability of brain tumors segmentation in multimodal Magnetic Resonance Imaging Tommaso Torda Andrea Ciardiello Simona Gargiulo Greta Grillo Simone Scardapane Cecilia Voena S. Giagu 19 0 0 05 Apr 2024
Accurate estimation of feature importance faithfulness for tree models Mateusz Gajewski Adam Karczmarz Mateusz Rapicki Piotr Sankowski 27 0 0 04 Apr 2024
ALMANACS: A Simulatability Benchmark for Language Model Explainability Edmund Mills Shiye Su Stuart J. Russell Scott Emmons 46 7 0 20 Dec 2023
Variable Importance in High-Dimensional Settings Requires Grouping Ahmad Chamma Bertrand Thirion D. Engemann 32 3 0 18 Dec 2023
An adversarial attack approach for eXplainable AI evaluation on deepfake detection models Balachandar Gowrisankar V. Thing AAML 26 11 0 08 Dec 2023
Occlusion Sensitivity Analysis with Augmentation Subspace Perturbation in Deep Feature Space Pedro Valois Koichiro Niinuma Kazuhiro Fukui AAML 24 4 0 25 Nov 2023
Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals Yanai Elazar Bhargavi Paranjape Hao Peng Sarah Wiegreffe Khyathi Raghavi Vivek Srikumar Sameer Singh Noah A. Smith AAML OOD 21 0 0 16 Nov 2023
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 23 2 0 09 Nov 2023
Advancing Post Hoc Case Based Explanation with Feature Highlighting Eoin M. Kenny Eoin Delaney Markt. Keane 26 5 0 06 Nov 2023
Intriguing Properties of Data Attribution on Diffusion Models Xiaosen Zheng Tianyu Pang Chao Du Jing Jiang Min-Bin Lin TDI 34 20 1 01 Nov 2023
Evaluating Explanation Methods for Vision-and-Language Navigation Guanqi Chen Lei Yang Guanhua Chen Jia Pan XAI 21 0 0 10 Oct 2023
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods Fred Zhang Neel Nanda LLMSV 26 96 0 27 Sep 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 80 7 0 14 Sep 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 32 32 0 11 Aug 2023
Precise Benchmarking of Explainable AI Attribution Methods Rafael Brandt Daan Raatjens G. Gaydadjiev XAI 19 4 0 06 Aug 2023
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability Usha Bhalla Suraj Srinivas Himabindu Lakkaraju FAtt CML 21 6 0 27 Jul 2023
Uncovering Unique Concept Vectors through Latent Space Decomposition Mara Graziani Laura Mahony An-phi Nguyen Henning Muller Vincent Andrearczyk 36 4 0 13 Jul 2023
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When? M. Rubaiyat Hossain Mondal Prajoy Podder 13 56 0 10 Apr 2023
Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation N. Jethani A. Saporta Rajesh Ranganath FAtt 29 10 0 24 Feb 2023
The Generalizability of Explanations Hanxiao Tan FAtt 8 1 0 23 Feb 2023
Less is More: The Influence of Pruning on the Explainability of CNNs David Weber F. Merkle Pascal Schöttle Stephan Schlögl Martin Nocker FAtt 29 1 0 17 Feb 2023
Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation Jack Furby Daniel Cunnington Dave Braines Alun D. Preece 6 6 0 07 Feb 2023
Explaining Imitation Learning through Frames Boyuan Zheng Jianlong Zhou Chun-Hao Liu Yiqiao Li Fang Chen 14 0 0 03 Jan 2023
Attribution-based XAI Methods in Computer Vision: A Review Kumar Abhishek Deeksha Kamath 27 16 0 27 Nov 2022
On Pitfalls of Measuring Occlusion Robustness through Data Distortion Antonia Marcu 8 0 0 24 Nov 2022
ModelDiff: A Framework for Comparing Learning Algorithms Harshay Shah Sung Min Park Andrew Ilyas A. Madry SyDa 46 26 0 22 Nov 2022
Explaining Image Classifiers with Multiscale Directional Image Representation Stefan Kolek Robert Windesheim Héctor Andrade-Loarca Gitta Kutyniok Ron Levie 16 4 0 22 Nov 2022
Easy to Decide, Hard to Agree: Reducing Disagreements Between Saliency Methods Josip Jukić Martin Tutek Jan Snajder FAtt 8 0 0 15 Nov 2022
Exploring Self-Attention for Crop-type Classification Explainability Ivica Obadic R. Roscher Dario Augusto Borges Oliveira Xiao Xiang Zhu 22 7 0 24 Oct 2022
Computing Abductive Explanations for Boosted Trees Gilles Audemard Jean-Marie Lagniez Pierre Marquis N. Szczepanski 24 12 0 16 Sep 2022
ferret: a Framework for Benchmarking Explainers on Transformers Giuseppe Attanasio Eliana Pastor C. Bonaventura Debora Nozza 28 30 0 02 Aug 2022
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence Isha Hameed Samuel Sharpe Daniel Barcklow Justin Au-yeung Sahil Verma Jocelyn Huang Brian Barr C. B. Bruss 30 14 0 12 Jul 2022
FRAME: Evaluating Rationale-Label Consistency Metrics for Free-Text Rationales Aaron Chan Shaoliang Nie Liang Tan Xiaochang Peng Hamed Firooz Maziar Sanjabi Xiang Ren 40 9 0 02 Jul 2022
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models Liu Zhendong Wenyu Jiang Yan Zhang Chongjun Wang CML 6 0 0 22 Jun 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 42 18 0 31 May 2022
Faithful Explanations for Deep Graph Models Zifan Wang Yuhang Yao Chaoran Zhang Han Zhang Youjie Kang Carlee Joe-Wong Matt Fredrikson Anupam Datta FAtt 14 2 0 24 May 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection Esma Balkir I. Nejadgholi Kathleen C. Fraser S. Kiritchenko FAtt 33 27 0 06 May 2022