The (Un)reliability of saliency methods

2 November 2017

Pieter-Jan Kindermans

Papers citing "The (Un)reliability of saliency methods"

50 / 118 papers shown

Title
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts M. Zarlenga Gabriele Dominici Pietro Barbiero Z. Shams M. Jamnik KELM 152 0 0 24 Apr 2025
Saliency-driven Dynamic Token Pruning for Large Language Models Yao Tao Yehui Tang Yun Wang Mingjian Zhu Hailin Hu Yunhe Wang 34 0 0 06 Apr 2025
Towards Responsible and Trustworthy Educational Data Mining: Comparing Symbolic, Sub-Symbolic, and Neural-Symbolic AI Methods Danial Hooshyar Eve Kikas Yeongwook Yang Gustav Šír Raija Hamalainen T. Karkkainen Roger Azevedo 56 1 0 01 Apr 2025
A Unified Framework with Novel Metrics for Evaluating the Effectiveness of XAI Techniques in LLMs Melkamu Mersha Mesay Gemeda Yigezu Hassan Shakil Ali Al shami SangHyun Byun Jugal Kalita 59 0 0 06 Mar 2025
Error-controlled non-additive interaction discovery in machine learning models Winston Chen Yifan Jiang William Stafford Noble Yang Young Lu 45 1 0 17 Feb 2025
Evaluating the Effectiveness of XAI Techniques for Encoder-Based Language Models Melkamu Mersha Mesay Gemeda Yigezu Jugal Kalita ELM 49 3 0 26 Jan 2025
GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease Wenjie Kang L. Jiskoot Peter De Deyn G. Biessels Huiberdina Koek ... H. Middelkoop W. M. van der Flier Willemijn J. Jansen S. Klein Esther E. Bron 29 0 0 20 Jan 2025
COMIX: Compositional Explanations using Prototypes S. Sivaprasad D. Kangin Plamen Angelov Mario Fritz 136 0 0 10 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
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models Jayneel Parekh Quentin Bouniot Pavlo Mozharovskyi A. Newson Florence dÁlché-Buc SSL 61 1 0 01 Jul 2024
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables James Hinns David Martens 41 2 0 24 May 2024
Robust Explainable Recommendation Sairamvinay Vijayaraghavan Prasant Mohapatra AAML 23 0 0 03 May 2024
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey Rokas Gipiškis Chun-Wei Tsai Olga Kurasova 54 5 0 02 May 2024
On the Value of Labeled Data and Symbolic Methods for Hidden Neuron Activation Analysis Abhilekha Dalal R. Rayan Adrita Barua Eugene Y. Vasserman Md Kamruzzaman Sarker Pascal Hitzler 27 4 0 21 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
3VL: Using Trees to Improve Vision-Language Models' Interpretability Nir Yellinek Leonid Karlinsky Raja Giryes CoGe VLM 49 4 0 28 Dec 2023
CAManim: Animating end-to-end network activation maps Emily Kaczmarek Olivier X. Miguel Alexa C. Bowie R. Ducharme Alysha L. J. Dingwall-Harvey S. Hawken Christine M. Armour Mark C. Walker Kevin Dick HAI 19 1 0 19 Dec 2023
CEIR: Concept-based Explainable Image Representation Learning Yan Cui Shuhong Liu Liuzhuozheng Li Zhiyuan Yuan SSL VLM 23 3 0 17 Dec 2023
Improving Interpretation Faithfulness for Vision Transformers Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang 24 5 0 29 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 28 2 0 09 Nov 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 80 7 0 14 Sep 2023
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI) Timo Speith Markus Langer 24 12 0 26 Jul 2023
Single-Class Target-Specific Attack against Interpretable Deep Learning Systems Eldor Abdukhamidov Mohammed Abuhamad George K. Thiruvathukal Hyoungshick Kim Tamer Abuhmed AAML 25 2 0 12 Jul 2023
Exploring the Lottery Ticket Hypothesis with Explainability Methods: Insights into Sparse Network Performance Shantanu Ghosh Kayhan Batmanghelich 30 0 0 07 Jul 2023
Are Deep Neural Networks Adequate Behavioural Models of Human Visual Perception? Felix Wichmann Robert Geirhos 32 25 0 26 May 2023
Take 5: Interpretable Image Classification with a Handful of Features Thomas Norrenbrock Marco Rudolph Bodo Rosenhahn FAtt 29 7 0 23 Mar 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 13 1 0 23 Feb 2023
Tell Model Where to Attend: Improving Interpretability of Aspect-Based Sentiment Classification via Small Explanation Annotations Zhenxiao Cheng Jie Zhou Wen Wu Qin Chen Liang He 22 3 0 21 Feb 2023
sMRI-PatchNet: A novel explainable patch-based deep learning network for Alzheimer's disease diagnosis and discriminative atrophy localisation with Structural MRI Xin Zhang Liangxiu Han Lianghao Han Haoming Chen Darren Dancey Daoqiang Zhang MedIm 13 4 0 17 Feb 2023
On The Coherence of Quantitative Evaluation of Visual Explanations Benjamin Vandersmissen José Oramas XAI FAtt 26 3 0 14 Feb 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 40 3 0 07 Feb 2023
Variational Information Pursuit for Interpretable Predictions Aditya Chattopadhyay Kwan Ho Ryan Chan B. Haeffele D. Geman René Vidal DRL 15 10 0 06 Feb 2023
Towards Reconciling Usability and Usefulness of Explainable AI Methodologies Pradyumna Tambwekar Matthew C. Gombolay 28 8 0 13 Jan 2023
Valid P-Value for Deep Learning-Driven Salient Region Daiki Miwa Vo Nguyen Le Duy I. Takeuchi FAtt AAML 19 14 0 06 Jan 2023
Interpretable ML for Imbalanced Data Damien Dablain C. Bellinger Bartosz Krawczyk D. Aha Nitesh V. Chawla 22 1 0 15 Dec 2022
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 24 14 0 13 Dec 2022
This changes to that : Combining causal and non-causal explanations to generate disease progression in capsule endoscopy Anuja Vats A. Mohammed Marius Pedersen Nirmalie Wiratunga MedIm 22 9 0 05 Dec 2022
Understanding and Enhancing Robustness of Concept-based Models Sanchit Sinha Mengdi Huai Jianhui Sun Aidong Zhang AAML 25 18 0 29 Nov 2022
Towards More Robust Interpretation via Local Gradient Alignment Sunghwan Joo Seokhyeon Jeong Juyeon Heo Adrian Weller Taesup Moon FAtt 25 5 0 29 Nov 2022
Attribution-based XAI Methods in Computer Vision: A Review Kumar Abhishek Deeksha Kamath 27 18 0 27 Nov 2022
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 16 8 0 23 Nov 2022
Explaining Image Classifiers with Multiscale Directional Image Representation Stefan Kolek Robert Windesheim Héctor Andrade-Loarca Gitta Kutyniok Ron Levie 26 4 0 22 Nov 2022
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
Easy to Decide, Hard to Agree: Reducing Disagreements Between Saliency Methods Josip Jukić Martin Tutek Jan Snajder FAtt 16 0 0 15 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 29 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
Explainable Deep Learning to Profile Mitochondrial Disease Using High Dimensional Protein Expression Data Atif Khan C. Lawless Amy Vincent Satish Pilla S. Ramesh A. Mcgough 28 0 0 31 Oct 2022
The Influence of Explainable Artificial Intelligence: Nudging Behaviour or Boosting Capability? Matija Franklin TDI 21 1 0 05 Oct 2022
A model-agnostic approach for generating Saliency Maps to explain inferred decisions of Deep Learning Models S. Karatsiolis A. Kamilaris FAtt 29 1 0 19 Sep 2022