The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples

11 September 2020

Papers citing "The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples"

29 / 29 papers shown

Title
Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks Jeremy Goldwasser Giles Hooker AAML 24 0 0 21 Apr 2025
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification Jonas Teufel Annika Leinweber Pascal Friederich 44 0 0 03 Apr 2025
Guidelines For The Choice Of The Baseline in XAI Attribution Methods Cristian Morasso Giorgio Dolci I. Galazzo Sergey M. Plis Gloria Menegaz 37 0 0 25 Mar 2025
All You Need for Counterfactual Explainability Is Principled and Reliable Estimate of Aleatoric and Epistemic Uncertainty Kacper Sokol Eyke Hüllermeier 51 2 0 24 Feb 2025
Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization Keita Kinjo 29 1 0 10 Jan 2025
Faithfulness and the Notion of Adversarial Sensitivity in NLP Explanations Supriya Manna Niladri Sett AAML 29 2 0 26 Sep 2024
CF-OPT: Counterfactual Explanations for Structured Prediction Germain Vivier--Ardisson Alexandre Forel Axel Parmentier Thibaut Vidal OffRL CML BDL 30 1 0 28 May 2024
Trustworthy Actionable Perturbations Jesse Friedbaum S. Adiga Ravi Tandon AAML 28 2 0 18 May 2024
Do Counterfactual Examples Complicate Adversarial Training? Eric C. Yeats Cameron Darwin Eduardo Ortega Frank Liu Hai Li DiffM 30 0 0 16 Apr 2024
CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests Susanne Dandl Kristin Blesch Timo Freiesleben Gunnar Konig Jan Kapar B. Bischl Marvin N. Wright AAML 27 5 0 04 Apr 2024
Machine Learning Robustness: A Primer Houssem Ben Braiek Foutse Khomh AAML OOD 24 5 0 01 Apr 2024
Towards Non-Adversarial Algorithmic Recourse Tobias Leemann Martin Pawelczyk Bardh Prenkaj Gjergji Kasneci AAML 21 0 0 15 Mar 2024
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge L. Fenaux Florian Kerschbaum AAML 29 0 0 22 Feb 2024
Fragility, Robustness and Antifragility in Deep Learning Chandresh Pravin Ivan Martino Giuseppe Nicosia Varun Ojha 8 0 0 15 Dec 2023
Artificial Neural Nets and the Representation of Human Concepts Timo Freiesleben NAI 9 1 0 08 Dec 2023
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion Jialin Chen Shirley Wu Abhijit Gupta Rex Ying DiffM 18 4 0 30 Oct 2023
Generating collective counterfactual explanations in score-based classification via mathematical optimization E. Carrizosa Jasone Ramírez-Ayerbe Dolores Romero Morales 21 18 0 19 Oct 2023
On the Trade-offs between Adversarial Robustness and Actionable Explanations Satyapriya Krishna Chirag Agarwal Himabindu Lakkaraju AAML 14 0 0 28 Sep 2023
counterfactuals: An R Package for Counterfactual Explanation Methods Susanne Dandl Andreas Hofheinz Martin Binder B. Bischl Giuseppe Casalicchio 19 2 0 13 Apr 2023
Clarity: an improved gradient method for producing quality visual counterfactual explanations Claire Theobald Frédéric Pennerath Brieuc Conan-Guez Miguel Couceiro Amedeo Napoli BDL 28 0 0 22 Nov 2022
Interpretation of Black Box NLP Models: A Survey Shivani Choudhary N. Chatterjee S. K. Saha FAtt 23 10 0 31 Mar 2022
Towards Explainable Evaluation Metrics for Natural Language Generation Christoph Leiter Piyawat Lertvittayakumjorn M. Fomicheva Wei-Ye Zhao Yang Gao Steffen Eger AAML ELM 19 20 0 21 Mar 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 19 36 0 22 Jan 2022
A Causal Perspective on Meaningful and Robust Algorithmic Recourse Gunnar Konig Timo Freiesleben Moritz Grosse-Wentrup 17 16 0 16 Jul 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 12 94 0 02 Mar 2021
Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data F. Cartella Orlando Anunciação Yuki Funabiki D. Yamaguchi Toru Akishita Olivier Elshocht AAML 48 71 0 20 Jan 2021
Transferable Adversarial Attacks for Image and Video Object Detection Xingxing Wei Siyuan Liang Ning Chen Xiaochun Cao AAML 72 220 0 30 Nov 2018
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 250 5,813 0 08 Jul 2016