Unmasking Clever Hans Predictors and Assessing What Machines Really Learn

26 February 2019

Papers citing "Unmasking Clever Hans Predictors and Assessing What Machines Really Learn"

50 / 107 papers shown

Title
Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena Philip Naumann Jacob R. Kauffmann G. Montavon 24 0 0 09 May 2025
Interactive Medical Image Analysis with Concept-based Similarity Reasoning Ta Duc Huy Sen Kim Tran Phan Nguyen Nguyen Hoang Tran Tran Bao Sam A. Hengel Zhibin Liao Johan W. Verjans Minh Nguyen Nhat To Vu Minh Hieu Phan 41 0 0 10 Mar 2025
Do ImageNet-trained models learn shortcuts? The impact of frequency shortcuts on generalization Shunxin Wang Raymond N. J. Veldhuis N. Strisciuglio VLM 71 0 0 05 Mar 2025
The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation Martin Mundt Anaelia Ovalle Felix Friedrich A Pranav Subarnaduti Paul Manuel Brack Kristian Kersting William Agnew 265 0 0 05 Feb 2025
Pfungst and Clever Hans: Identifying the unintended cues in a widely used Alzheimer's disease MRI dataset using explainable deep learning C. Tinauer Maximilian Sackl Rudolf Stollberger Stefan Ropele C. Langkammer AAML 35 0 0 27 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
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers Lam Nguyen Tung Steven Cho Xiaoning Du Neelofar Neelofar Valerio Terragni Stefano Ruberto Aldeida Aleti 127 2 0 30 Oct 2024
Study on the Helpfulness of Explainable Artificial Intelligence Tobias Labarta Elizaveta Kulicheva Ronja Froelian Christian Geißler Xenia Melman Julian von Klitzing ELM 31 0 0 14 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
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Hugo Porta Emanuele Dalsasso Diego Marcos D. Tuia 93 0 0 14 Sep 2024
Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics Charlotte Beylier Simon M. Hofmann Nico Scherf 26 0 0 20 Jun 2024
MambaLRP: Explaining Selective State Space Sequence Models F. Jafari G. Montavon Klaus-Robert Müller Oliver Eberle Mamba 54 9 0 11 Jun 2024
Language-guided Detection and Mitigation of Unknown Dataset Bias Zaiying Zhao Soichiro Kumano Toshihiko Yamasaki 36 2 0 05 Jun 2024
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables James Hinns David Martens 41 2 0 24 May 2024
Explaining Text Similarity in Transformer Models Alexandros Vasileiou Oliver Eberle 43 7 0 10 May 2024
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients Evandro S. Ortigossa Fábio F. Dias Brian Barr Claudio T. Silva L. G. Nonato FAtt 54 2 0 25 Apr 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 34 5 0 11 Mar 2024
Implementing local-explainability in Gradient Boosting Trees: Feature Contribution Ángel Delgado-Panadero Beatriz Hernández-Lorca María Teresa García-Ordás J. Benítez-Andrades 32 52 0 14 Feb 2024
RudolfV: A Foundation Model by Pathologists for Pathologists Jonas Dippel Barbara Feulner Tobias Winterhoff Timo Milbich Stephan Tietz ... David Horst Lukas Ruff Klaus-Robert Muller Frederick Klauschen Maximilian Alber 25 28 0 08 Jan 2024
Towards Interpretable Classification of Leukocytes based on Deep Learning S. Röhrl Johannes Groll M. Lengl Simon Schumann C. Klenk D. Heim Martin Knopp Oliver Hayden Klaus Diepold 25 2 0 24 Nov 2023
Labeling Neural Representations with Inverse Recognition Kirill Bykov Laura Kopf Shinichi Nakajima Marius Kloft Marina M.-C. Höhne BDL 19 15 0 22 Nov 2023
Rethinking the Evaluating Framework for Natural Language Understanding in AI Systems: Language Acquisition as a Core for Future Metrics Patricio Vera Pedro Moya Lisa Barraza ELM 16 1 0 21 Sep 2023
What, Indeed, is an Achievable Provable Guarantee for Learning-Enabled Safety Critical Systems Saddek Bensalem Chih-Hong Cheng Wei Huang Xiaowei Huang Changshun Wu Xingyu Zhao AAML 19 6 0 20 Jul 2023
A Vulnerability of Attribution Methods Using Pre-Softmax Scores Miguel A. Lerma Mirtha Lucas FAtt 14 0 0 06 Jul 2023
Improving neural network representations using human similarity judgments Lukas Muttenthaler Lorenz Linhardt Jonas Dippel Robert A. Vandermeulen Katherine L. Hermann Andrew Kyle Lampinen Simon Kornblith 40 29 0 07 Jun 2023
One Explanation Does Not Fit XIL Felix Friedrich David Steinmann Kristian Kersting LRM 35 2 0 14 Apr 2023
Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategy David Schlangen ELM 21 12 0 14 Apr 2023
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks Lorenz Linhardt Klaus-Robert Muller G. Montavon AAML 21 7 0 12 Apr 2023
Mark My Words: Dangers of Watermarked Images in ImageNet Kirill Bykov Klaus-Robert Muller Marina M.-C. Höhne 40 4 0 09 Mar 2023
On the contribution of pre-trained models to accuracy and utility in modeling distributed energy resources H. Kazmi Pierre Pinson 11 0 0 22 Feb 2023
SpecXAI -- Spectral interpretability of Deep Learning Models Stefan Druc Peter Wooldridge A. Krishnamurthy S. Sarkar Aditya Balu 17 0 0 20 Feb 2023
On The Coherence of Quantitative Evaluation of Visual Explanations Benjamin Vandersmissen José Oramas XAI FAtt 21 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 37 3 0 07 Feb 2023
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity Vincent Souveton Arnaud Guillin J. Jasche G. Lavaux Manon Michel 18 3 0 03 Feb 2023
Cluster-CAM: Cluster-Weighted Visual Interpretation of CNNs' Decision in Image Classification Zhenpeng Feng H. Ji M. Daković Xiyang Cui Mingzhe Zhu Ljubisa Stankovic 19 7 0 03 Feb 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
Topical Hidden Genome: Discovering Latent Cancer Mutational Topics using a Bayesian Multilevel Context-learning Approach Saptarshi Chakraborty Zoe Guan C. Begg R. Shen 16 2 0 30 Dec 2022
Criteria for Classifying Forecasting Methods Tim Januschowski Jan Gasthaus Bernie Wang David Salinas Valentin Flunkert Michael Bohlke-Schneider Laurent Callot AI4TS 21 173 0 07 Dec 2022
Localized Shortcut Removal Nicolas M. Muller Jochen Jacobs Jennifer Williams Konstantin Böttinger 19 0 0 24 Nov 2022
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria Theresa Bender J. Beinecke D. Krefting Carolin Müller Henning Dathe T. Seidler Nicolai Spicher Anne-Christin Hauschild FAtt 11 24 0 03 Nov 2022
The Debate Over Understanding in AI's Large Language Models Melanie Mitchell D. Krakauer ELM 74 202 0 14 Oct 2022
Shortcut Learning of Large Language Models in Natural Language Understanding Mengnan Du Fengxiang He Na Zou Dacheng Tao Xia Hu KELM OffRL 28 83 0 25 Aug 2022
Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning Olivia Wiles Isabela Albuquerque Sven Gowal VLM 30 46 0 18 Aug 2022
How Robust is Unsupervised Representation Learning to Distribution Shift? Yuge Shi Imant Daunhawer Julia E. Vogt Philip H. S. Torr Amartya Sanyal OOD 30 25 0 17 Jun 2022
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation Reduan Achtibat Maximilian Dreyer Ilona Eisenbraun S. Bosse Thomas Wiegand Wojciech Samek Sebastian Lapuschkin FAtt 25 131 0 07 Jun 2022
Optimizing Relevance Maps of Vision Transformers Improves Robustness Hila Chefer Idan Schwartz Lior Wolf ViT 27 37 0 02 Jun 2022
One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks Shutong Wu Sizhe Chen Cihang Xie X. Huang AAML 40 26 0 24 May 2022
Perception Visualization: Seeing Through the Eyes of a DNN Loris Giulivi Mark J. Carman Giacomo Boracchi 13 6 0 21 Apr 2022
Backdooring Explainable Machine Learning Maximilian Noppel Lukas Peter Christian Wressnegger AAML 14 5 0 20 Apr 2022
Explainable Analysis of Deep Learning Methods for SAR Image Classification Sheng Su Ziteng Cui Weiwei Guo Zenghui Zhang Wenxian Yu XAI 25 12 0 14 Apr 2022