Counterfactual Explanations Can Be Manipulated

4 June 2021

Himabindu Lakkaraju

Papers citing "Counterfactual Explanations Can Be Manipulated"

39 / 39 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 45 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 88 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 71 0 0 31 Mar 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 18 3 0 18 Feb 2025
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs Chhavi Yadav Evan Monroe Laufer Dan Boneh Kamalika Chaudhuri 100 0 0 06 Feb 2025
Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization Keita Kinjo 65 1 0 10 Jan 2025
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 68 1 0 29 Oct 2024
S-CFE: Simple Counterfactual Explanations Shpresim Sadiku Moritz Wagner Sai Ganesh Nagarajan Sebastian Pokutta 59 0 0 21 Oct 2024
Time Can Invalidate Algorithmic Recourse Giovanni De Toni Stefano Teso Bruno Lepri Andrea Passerini 49 0 0 10 Oct 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 48 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 51 7 0 29 Apr 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 63 18 0 28 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 56 2 0 19 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks Vasisht Duddu S. Szyller Nadarajah Asokan AAML 60 2 0 07 Dec 2023
Can AI Mitigate Human Perceptual Biases? A Pilot Study Ross Geuy Nate Rising Tiancheng Shi Meng-Ying Ling Jian Chen 38 0 0 10 Oct 2023
Explaining Black-Box Models through Counterfactuals Patrick Altmeyer A. V. Deursen Cynthia C. S. Liem CML LRM 53 2 0 14 Aug 2023
GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations Dan Ley Saumitra Mishra Daniele Magazzeni LRM 56 16 0 26 May 2023
Algorithmic Recourse with Missing Values Kentaro Kanamori Takuya Takagi Ken Kobayashi Yuichi Ike 41 2 0 28 Apr 2023
Impact Of Explainable AI On Cognitive Load: Insights From An Empirical Study L. Herm 26 22 0 18 Apr 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals Greta Warren Markt. Keane Christophe Guéret Eoin Delaney 39 13 0 16 Mar 2023
"How to make them stay?" -- Diverse Counterfactual Explanations of Employee Attrition André Artelt Andreas Gregoriades 54 5 0 08 Mar 2023
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse Zijie J. Wang J. W. Vaughan R. Caruana Duen Horng Chau HAI 41 22 0 27 Feb 2023
Finding Regions of Counterfactual Explanations via Robust Optimization Donato Maragno Jannis Kurtz Tabea E. Rober Rob Goedhart cS. .Ilker Birbil D. Hertog 75 22 0 26 Jan 2023
Don't Lie to Me: Avoiding Malicious Explanations with STEALTH Lauren Alvarez Tim Menzies 54 2 0 25 Jan 2023
"Explain it in the Same Way!" -- Model-Agnostic Group Fairness of Counterfactual Explanations André Artelt Barbara Hammer FaML 54 8 0 27 Nov 2022
Formalising the Robustness of Counterfactual Explanations for Neural Networks Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni AAML 34 27 0 31 Aug 2022
Inferring Sensitive Attributes from Model Explanations Vasisht Duddu A. Boutet MIACV SILM 33 17 0 21 Aug 2022
Global Counterfactual Explanations: Investigations, Implementations and Improvements Dan Ley Saumitra Mishra Daniele Magazzeni LRM 66 12 0 14 Apr 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse Martin Pawelczyk Teresa Datta Johannes van-den-Heuvel Gjergji Kasneci Himabindu Lakkaraju 29 38 0 13 Mar 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 33 41 0 15 Feb 2022
Framework for Evaluating Faithfulness of Local Explanations S. Dasgupta Nave Frost Michal Moshkovitz FAtt 149 61 0 01 Feb 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts Sebastian Bordt Michèle Finck Eric Raidl U. V. Luxburg AILaw 69 78 0 25 Jan 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 41 36 0 22 Jan 2022
On the Adversarial Robustness of Causal Algorithmic Recourse Ricardo Dominguez-Olmedo Amir-Hossein Karimi Bernhard Schölkopf 53 63 0 21 Dec 2021
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions Prateek Yadav Peter Hase Joey Tianyi Zhou 32 11 0 01 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations Saumitra Mishra Sanghamitra Dutta Jason Long Daniele Magazzeni AAML 27 57 0 30 Oct 2021
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 33 166 0 20 Oct 2020
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference Disi Ji Padhraic Smyth M. Steyvers 44 45 0 19 Oct 2020
On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen Amir-Hossein Karimi Umang Bhatt Isabel Valera Adrian Weller Bernhard Schölkopf FaML 82 85 0 13 Oct 2020