On the (In)fidelity and Sensitivity for Explanations

27 January 2019

David I. Inouye

Papers citing "On the (In)fidelity and Sensitivity for Explanations"

50 / 69 papers shown

Title
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review Sonal Allana Mohan Kankanhalli Rozita Dara 27 0 0 05 May 2025
Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods Mahdi Dhaini Ege Erdogan Nils Feldhus Gjergji Kasneci 41 0 0 02 May 2025
Axiomatic Explainer Globalness via Optimal Transport Davin Hill Josh Bone A. Masoomi Max Torop Jennifer Dy 95 1 0 13 Mar 2025
Interpretable High-order Knowledge Graph Neural Network for Predicting Synthetic Lethality in Human Cancers Xuexin Chen Ruichu Cai Zhengting Huang Zijian Li Jie Zheng Min Wu 41 0 0 08 Mar 2025
XEQ Scale for Evaluating XAI Experience Quality A. Wijekoon Nirmalie Wiratunga D. Corsar Kyle Martin Ikechukwu Nkisi-Orji Belén Díaz-Agudo Derek Bridge 44 2 0 20 Jan 2025
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics Lukas Klein Carsten T. Lüth U. Schlegel Till J. Bungert Mennatallah El-Assady Paul F. Jäger XAI ELM 34 2 0 03 Jan 2025
A Tale of Two Imperatives: Privacy and Explainability Supriya Manna Niladri Sett 91 0 0 30 Dec 2024
A Fresh Look at Sanity Checks for Saliency Maps Anna Hedström Leander Weber Sebastian Lapuschkin Marina M.-C. Höhne FAtt LRM 37 5 0 03 May 2024
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey Rokas Gipiškis Chun-Wei Tsai Olga Kurasova 52 5 0 02 May 2024
Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training Shizhan Gong Qi Dou Farzan Farnia FAtt 35 2 0 06 Apr 2024
Accurate estimation of feature importance faithfulness for tree models Mateusz Gajewski Adam Karczmarz Mateusz Rapicki Piotr Sankowski 32 0 0 04 Apr 2024
What Sketch Explainability Really Means for Downstream Tasks Hmrishav Bandyopadhyay Pinaki Nath Chowdhury A. Bhunia Aneeshan Sain Tao Xiang Yi-Zhe Song 30 4 0 14 Mar 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation Xuexin Chen Ruichu Cai Zhengting Huang Yuxuan Zhu Julien Horwood Zhifeng Hao Zijian Li Jose Miguel Hernandez-Lobato AAML 36 2 0 13 Feb 2024
A comprehensive study on fidelity metrics for XAI Miquel Miró-Nicolau Antoni Jaume-i-Capó Gabriel Moyà Alcover 25 11 0 19 Jan 2024
Manifold-based Shapley for SAR Recognization Network Explanation Xuran Hu Mingzhe Zhu Yuanjing Liu Zhenpeng Feng Ljubiša Stanković FAtt GAN 15 3 0 06 Jan 2024
An adversarial attack approach for eXplainable AI evaluation on deepfake detection models Balachandar Gowrisankar V. Thing AAML 26 11 0 08 Dec 2023
Improving Interpretation Faithfulness for Vision Transformers Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang 21 5 0 29 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
Beyond XAI:Obstacles Towards Responsible AI Yulu Pi 32 2 0 07 Sep 2023
Precise Benchmarking of Explainable AI Attribution Methods Rafael Brandt Daan Raatjens G. Gaydadjiev XAI 19 4 0 06 Aug 2023
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI) Timo Speith Markus Langer 24 12 0 26 Jul 2023
Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition Xiao-lan Wu P. Bell A. Rajan 19 5 0 29 May 2023
Towards Evaluating Explanations of Vision Transformers for Medical Imaging Piotr Komorowski Hubert Baniecki P. Biecek MedIm 31 27 0 12 Apr 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 28 22 0 17 Jan 2023
Impossibility Theorems for Feature Attribution Blair Bilodeau Natasha Jaques Pang Wei Koh Been Kim FAtt 18 68 0 22 Dec 2022
Truthful Meta-Explanations for Local Interpretability of Machine Learning Models Ioannis Mollas Nick Bassiliades Grigorios Tsoumakas 16 3 0 07 Dec 2022
SEAT: Stable and Explainable Attention Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang OOD 18 18 0 23 Nov 2022
Data-Centric Debugging: mitigating model failures via targeted data collection Sahil Singla Atoosa Malemir Chegini Mazda Moayeri Soheil Feiz 14 4 0 17 Nov 2022
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Zixi Chen Varshini Subhash Marton Havasi Weiwei Pan Finale Doshi-Velez XAI FAtt 27 18 0 10 Nov 2022
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Privacy Meets Explainability: A Comprehensive Impact Benchmark S. Saifullah Dominique Mercier Adriano Lucieri Andreas Dengel Sheraz Ahmed 19 14 0 08 Nov 2022
EMaP: Explainable AI with Manifold-based Perturbations Minh Nhat Vu Huy Mai My T. Thai AAML 35 2 0 18 Sep 2022
ScoreCAM GNN: une explication optimale des réseaux profonds sur graphes Adrien Raison Pascal Bourdon David Helbert FAtt GNN 19 0 0 26 Jul 2022
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification Khiem H. Le Hieu H. Pham Thao BT. Nguyen Tu Nguyen T. Thanh Cuong D. Do 13 34 0 25 Jul 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
Interpretability of Machine Learning Methods Applied to Neuroimaging Elina Thibeau-Sutre S. Collin Ninon Burgos O. Colliot 13 4 0 14 Apr 2022
Explainable Analysis of Deep Learning Methods for SAR Image Classification Sheng Su Ziteng Cui Weiwei Guo Zenghui Zhang Wenxian Yu XAI 20 12 0 14 Apr 2022
Human-Centered Concept Explanations for Neural Networks Chih-Kuan Yeh Been Kim Pradeep Ravikumar FAtt 22 25 0 25 Feb 2022
First is Better Than Last for Language Data Influence Chih-Kuan Yeh Ankur Taly Mukund Sundararajan Frederick Liu Pradeep Ravikumar TDI 17 20 0 24 Feb 2022
Evaluating Feature Attribution Methods in the Image Domain Arne Gevaert Axel-Jan Rousseau Thijs Becker D. Valkenborg T. D. Bie Yvan Saeys FAtt 6 22 0 22 Feb 2022
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis Thomas Fel Mélanie Ducoffe David Vigouroux Rémi Cadène Mikael Capelle C. Nicodeme Thomas Serre AAML 18 41 0 15 Feb 2022
Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods Dominique Mercier Jwalin Bhatt Andreas Dengel Sheraz Ahmed AI4TS 9 11 0 08 Feb 2022
Towards a consistent interpretation of AIOps models Yingzhe Lyu Gopi Krishnan Rajbahadur Dayi Lin Boyuan Chen Zhen Ming Z. Jiang AI4CE 14 19 0 04 Feb 2022
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 31 55 0 05 Dec 2021
Defense Against Explanation Manipulation Ruixiang Tang Ninghao Liu Fan Yang Na Zou Xia Hu AAML 39 11 0 08 Nov 2021
Coalitional Bayesian Autoencoders -- Towards explainable unsupervised deep learning Bang Xiang Yong Alexandra Brintrup 19 6 0 19 Oct 2021
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models S. Chatterjee Arnab Das Chirag Mandal Budhaditya Mukhopadhyay Manish Vipinraj Aniruddh Shukla R. Rao Chompunuch Sarasaen Oliver Speck A. Nürnberger MedIm 21 14 0 16 Oct 2021
Diagnostics-Guided Explanation Generation Pepa Atanasova J. Simonsen Christina Lioma Isabelle Augenstein LRM FAtt 36 6 0 08 Sep 2021
A Survey on Automated Fact-Checking Zhijiang Guo M. Schlichtkrull Andreas Vlachos 27 456 0 26 Aug 2021
Semantic Concentration for Domain Adaptation Shuang Li Mixue Xie Fangrui Lv Chi Harold Liu Jian Liang C. Qin Wei Li 52 87 0 12 Aug 2021