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Counterfactual Explanations Can Be Manipulated

4 June 2021

Himabindu Lakkaraju

Papers citing "Counterfactual Explanations Can Be Manipulated"

50 / 89 papers shown

Title
A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability Pouria Fatemi Ehsan Sharifian Mohammad Hossein Yassaee 131 0 0 05 May 2025
Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration Vasiliki Papanikou Danae Pla Karidi E. Pitoura Emmanouil Panagiotou Eirini Ntoutsi 158 0 0 01 May 2025
When Counterfactual Reasoning Fails: Chaos and Real-World Complexity Yahya Aalaila Gerrit Großmann Sumantrak Mukherjee Jonas Wahl Sebastian Vollmer CML LRM 144 0 0 31 Mar 2025
Can LLMs Explain Themselves Counterfactually? Zahra Dehghanighobadi Asja Fischer Muhammad Bilal Zafar LRM 88 0 0 25 Feb 2025
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models Thomas Fel Ekdeep Singh Lubana Jacob S. Prince M. Kowal Victor Boutin Isabel Papadimitriou Binxu Wang Martin Wattenberg Demba Ba Talia Konkle 76 8 0 18 Feb 2025
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs Chhavi Yadav Evan Monroe Laufer Dan Boneh Kamalika Chaudhuri 205 0 0 06 Feb 2025
Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization Keita Kinjo 113 1 0 10 Jan 2025
Utilizing Human Behavior Modeling to Manipulate Explanations in AI-Assisted Decision Making: The Good, the Bad, and the Scary Zhuoyan Li Ming Yin 67 3 0 02 Nov 2024
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 227 1 0 29 Oct 2024
S-CFE: Simple Counterfactual Explanations Shpresim Sadiku Moritz Wagner Sai Ganesh Nagarajan Sebastian Pokutta 141 1 0 21 Oct 2024
Time Can Invalidate Algorithmic Recourse Giovanni De Toni Stefano Teso Bruno Lepri Andrea Passerini 102 1 0 10 Oct 2024
Understanding with toy surrogate models in machine learning Andrés Páez SyDa 101 0 0 08 Oct 2024
Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse Yueqing Xuan Kacper Sokol Mark Sanderson Jeffrey Chan 72 1 0 03 Oct 2024
Learning-Augmented Robust Algorithmic Recourse Kshitij Kayastha Vasilis Gkatzelis Shahin Jabbari 84 0 0 02 Oct 2024
Review of Explainable Graph-Based Recommender Systems Thanet Markchom Huizhi Liang James Ferryman XAI 117 0 0 31 Jul 2024
CE-QArg: Counterfactual Explanations for Quantitative Bipolar Argumentation Frameworks (Technical Report) Xiang Yin Nico Potyka Francesca Toni 59 1 0 11 Jul 2024
Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations Luca Marzari Francesco Leofante Ferdinando Cicalese Alessandro Farinelli OOD 84 3 0 10 Jul 2024
Understanding Visual Feature Reliance through the Lens of Complexity Thomas Fel Louis Bethune Andrew Kyle Lampinen Thomas Serre Katherine Hermann FAtt CoGe 92 9 0 08 Jul 2024
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle Luca Deck Astrid Schomacker Timo Speith Jakob Schöffer Lena Kästner Niklas Kühl 76 4 0 29 Apr 2024
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots Xi Xin Giles Hooker Fei Huang AAML 71 7 0 29 Apr 2024
SIDEs: Separating Idealization from Deceptive Explanations in xAI Emily Sullivan 75 2 0 25 Apr 2024
Interval Abstractions for Robust Counterfactual Explanations Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni 60 1 0 21 Apr 2024
Forward Learning for Gradient-based Black-box Saliency Map Generation Zeliang Zhang Mingqian Feng Jinyang Jiang Rongyi Zhu Yijie Peng Chenliang Xu FAtt 103 2 0 22 Mar 2024
A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations André Artelt Andreas Gregoriades 61 1 0 02 Mar 2024
Axe the X in XAI: A Plea for Understandable AI Andrés Páez 91 0 0 01 Mar 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 286 22 0 28 Feb 2024
Cost-Adaptive Recourse Recommendation by Adaptive Preference Elicitation Duy Nguyen Bao Nguyen Viet Anh Nguyen 50 0 0 23 Feb 2024
The Effect of Data Poisoning on Counterfactual Explanations André Artelt Shubham Sharma Freddy Lecue Barbara Hammer 129 1 0 13 Feb 2024
Robust Counterfactual Explanations in Machine Learning: A Survey Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni OffRL CML 76 13 0 02 Feb 2024
SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 69 5 0 22 Dec 2023
Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation Nina Weng Paraskevas Pegios Eike Petersen Aasa Feragen Siavash Bigdeli MedIm CML 55 13 0 21 Dec 2023
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 158 3 0 19 Dec 2023
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals Patrick Altmeyer Mojtaba Farmanbar A. V. Deursen Cynthia C. S. Liem 64 3 0 17 Dec 2023
Promoting Counterfactual Robustness through Diversity Francesco Leofante Nico Potyka 37 8 0 11 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 162 2 0 07 Dec 2023
Privacy-Preserving Algorithmic Recourse Sikha Pentyala Shubham Sharma Sanjay Kariyappa Freddy Lecue Daniele Magazzeni 74 5 0 23 Nov 2023
A Critical Survey on Fairness Benefits of Explainable AI Luca Deck Jakob Schoeffer Maria De-Arteaga Niklas Kühl 117 13 0 15 Oct 2023
Can AI Mitigate Human Perceptual Biases? A Pilot Study Ross Geuy Nate Rising Tiancheng Shi Meng-Ying Ling Jian Chen 56 0 0 10 Oct 2023
Latent Diffusion Counterfactual Explanations Karim Farid Simon Schrodi Max Argus Thomas Brox DiffM 99 14 0 10 Oct 2023
On the Trade-offs between Adversarial Robustness and Actionable Explanations Satyapriya Krishna Chirag Agarwal Himabindu Lakkaraju AAML 84 0 0 28 Sep 2023
T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems Yiming Li Daling Wang Wenfang Wu Shi Feng Yifei Zhang CML 87 1 0 28 Sep 2023
Flexible and Robust Counterfactual Explanations with Minimal Satisfiable Perturbations Yongjie Wang Hangwei Qian Yongjie Liu Wei Guo Chunyan Miao 67 4 0 09 Sep 2023
Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse Edward A. Small Jeffrey N Clark Christopher J. McWilliams Kacper Sokol Jeffrey Chan Flora D. Salim Raúl Santos-Rodríguez 87 1 0 08 Sep 2023
Explaining Black-Box Models through Counterfactuals Patrick Altmeyer A. V. Deursen Cynthia C. S. Liem CML LRM 70 2 0 14 Aug 2023
CommonsenseVIS: Visualizing and Understanding Commonsense Reasoning Capabilities of Natural Language Models Xingbo Wang Renfei Huang Zhihua Jin Tianqing Fang Huamin Qu VLM ReLM LRM 109 2 0 23 Jul 2023
Stability Guarantees for Feature Attributions with Multiplicative Smoothing Anton Xue Rajeev Alur Eric Wong 117 6 0 12 Jul 2023
Simple Steps to Success: Axiomatics of Distance-Based Algorithmic Recourse Jenny Hamer Jake Valladares Vignesh Viswanathan Yair Zick 54 2 0 27 Jun 2023
Manipulation Risks in Explainable AI: The Implications of the Disagreement Problem S. Goethals David Martens Theodoros Evgeniou 88 4 0 24 Jun 2023
Hardness of Deceptive Certificate Selection Stephan Wäldchen AAML 29 1 0 07 Jun 2023
Adversarial attacks and defenses in explainable artificial intelligence: A survey Hubert Baniecki P. Biecek AAML 128 69 0 06 Jun 2023