Papers citing 'Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers'

Title
Actionable and diverse counterfactual explanations incorporating domain knowledge and causal constraints Szymon Bobek Łukasz Bałec Grzegorz J. Nalepa 12 0 0 25 Nov 2025
TriShGAN: Enhancing Sparsity and Robustness in Multivariate Time Series Counterfactuals Explanation Hongnan Ma Yiwei Shi Guanxiong Sun Mengyue Yang Weiru Liu AI4TS 94 0 0 09 Nov 2025
Towards Personalized Treatment Plan: Geometrical Model-Agnostic Approach to Counterfactual Explanations Daniel Sin Milad Toutounchian 158 0 0 27 Oct 2025
Synthesising Counterfactual Explanations via Label-Conditional Gaussian Mixture Variational Autoencoders Junqi Jiang Francesco Leofante Antonio Rago Francesca Toni CML 113 0 0 06 Oct 2025
ACE: Adapting sampling for Counterfactual Explanations Margarita A. Guerrero Cristian R. Rojas 94 1 0 30 Sep 2025
An Explainable Gaussian Process Auto-encoder for Tabular Data Wei Zhang Brian Barr John Paisley CML 118 1 0 31 Aug 2025
RealAC: A Domain-Agnostic Framework for Realistic and Actionable Counterfactual Explanations Asiful Arefeen Shovito Barua Soumma Hassan Ghasemzadeh CML 80 0 0 14 Aug 2025
Designing User-Centric Metrics for Evaluation of Counterfactual Explanations Firdaus Ahmed Choudhury Ethan Leicht Jude Ethan Bislig Hangzhi Guo A. Yadav 78 0 0 20 Jul 2025
Understanding Fixed Predictions via Confined Regions Connor Lawless Tsui-Wei Weng Berk Ustun Madeleine Udell 249 1 0 22 Feb 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning Numair Sani Daniel Malinsky I. Shpitser CML 762 16 0 10 Jan 2025
Counterfactual Explanations via Riemannian Latent Space Traversal Paraskevas Pegios Aasa Feragen Andreas Abildtrup Hansen Georgios Arvanitidis BDL 221 7 0 04 Nov 2024
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction Yinhan He Zaiyi Zheng Patrick Soga Yaozhen Zhu Yushun Dong Jundong Li 187 2 0 19 Oct 2024
HR-Bandit: Human-AI Collaborated Linear Recourse BanditInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Junyu Cao Ruijiang Gao Esmaeil Keyvanshokooh 486 4 0 18 Oct 2024
Good Data Is All Imitation Learning Needs Amir Samadi K. Koufos Kurt Debattista M. Dianati OffRL 181 3 0 26 Sep 2024
2D-OOB: Attributing Data Contribution through Joint Valuation FrameworkNeural Information Processing Systems (NeurIPS), 2024 Yifan Sun Jingyan Shen Yongchan Kwon TDI 323 4 0 07 Aug 2024
Watermarking Counterfactual Explanations Hangzhi Guo Amulya Yadav AAML 180 0 0 29 May 2024
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows Patryk Wielopolski Oleksii Furman Jerzy Stefanowski Maciej Ziȩba 253 7 0 27 May 2024
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels Patryk Wielopolski Oleksii Furman Łukasz Lenkiewicz Jerzy Stefanowski Maciej Ziȩba 335 5 0 27 May 2024
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark Fredrik D. Johansson CML 209 0 0 25 May 2024
Trustworthy Actionable PerturbationsInternational Conference on Machine Learning (ICML), 2024 Jesse Friedbaum Sudarshan Adiga Ravi Tandon AAML 224 2 0 18 May 2024
A Framework for Feasible Counterfactual Exploration incorporating Causality, Sparsity and Density Dimitris Sacharidis Dimitris Fotakis V. Kalogeraki Dimitrios Gunopulos CML 177 0 0 20 Apr 2024
Model-Based Counterfactual Explanations Incorporating Feature Space Attributes for Tabular Data Yuta Sumiya Hayaru Shouno AAML OOD 158 0 0 20 Apr 2024
Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence M. Domnich Raul Vicente 159 4 0 19 Apr 2024
Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration Seyedehdelaram Esfahani Giovanni De Toni Bruno Lepri Baptiste Caramiaux Katya Tentori Massimo Zancanaro 227 8 0 08 Apr 2024
CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests Susanne Dandl Kristin Blesch Timo Freiesleben Gunnar Konig Jan Kapar J. Herbinger Marvin N. Wright AAML 273 6 0 04 Apr 2024
Causal Feature Selection for Responsible Machine Learning Raha Moraffah Paras Sheth Saketh Vishnubhatla Huan Liu CML 167 3 0 05 Feb 2024
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data AttributionNeural Information Processing Systems (NeurIPS), 2024 Ian Covert Chanwoo Kim Su-In Lee James Zou Tatsunori Hashimoto TDI 281 14 0 29 Jan 2024
Generating Likely Counterfactuals Using Sum-Product NetworksInternational Conference on Learning Representations (ICLR), 2024 Jiri Nemecek Tomás Pevný Georgios Korpas TPM 499 4 0 25 Jan 2024
Causal Generative Explainers using Counterfactual Inference: A Case Study on the Morpho-MNIST DatasetPattern Analysis and Applications (PAA), 2024 William Taylor-Melanson Zahra Sadeghi Stan Matwin CML 167 7 0 21 Jan 2024
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals Patrick Altmeyer Mojtaba Farmanbar A. V. Deursen Cynthia C. S. Liem 132 6 0 17 Dec 2023
Learning impartial policies for sequential counterfactual explanations using Deep Reinforcement Learning E. Panagiotou Eirini Ntoutsi CML OffRL BDL 189 0 0 01 Nov 2023
Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach BDL 420 9 0 11 Oct 2023
Towards Feasible Counterfactual Explanations: A Taxonomy Guided Template-based NLG MethodEuropean Conference on Artificial Intelligence (ECAI), 2023 Pedram Salimi Nirmalie Wiratunga D. Corsar A. Wijekoon 154 2 0 03 Oct 2023
Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations Asiful Arefeen Hassan Ghasemzadeh 179 5 0 02 Oct 2023
On the Trade-offs between Adversarial Robustness and Actionable ExplanationsAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2023 Satyapriya Krishna Chirag Agarwal Himabindu Lakkaraju AAML 213 1 0 28 Sep 2023
Towards LLM-guided Causal Explainability for Black-box Text Classifiers Amrita Bhattacharjee Raha Moraffah Joshua Garland Huan Liu 235 47 0 23 Sep 2023
Towards User Guided Actionable RecourseAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2023 Jayanth Yetukuri Ian Hardy Yang Liu 145 4 0 05 Sep 2023
Prediction without Preclusion: Recourse Verification with Reachable SetsInternational Conference on Learning Representations (ICLR), 2023 Avni Kothari B. Kulynych Tsui-Wei Weng Berk Ustun FaML 253 7 0 24 Aug 2023
SafeAR: Safe Algorithmic Recourse by Risk-Aware PoliciesAAAI Conference on Artificial Intelligence (AAAI), 2023 Haochen Wu Sanjay Kariyappa Sunandita Patra Sriram Gopalakrishnan 253 1 0 23 Aug 2023
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained ModelsInternational Conference on Learning Representations (ICLR), 2023 Peiyan Zhang Hao Liu Chaozhuo Li Xing Xie Sunghun Kim Haohan Wang VLM OOD 292 9 0 21 Aug 2023
Assessing Systematic Weaknesses of DNNs using CounterfactualsAI and Ethics (AE), 2023 Sujan Sai Gannamaneni Michael Mock Maram Akila AAML 176 4 0 03 Aug 2023
Counterfactual Explanation Policies in RL Shripad Deshmukh R Srivatsan Supriti Vijay Jayakumar Subramanian Chirag Agarwal OffRL 193 0 0 25 Jul 2023
Simple Steps to Success: Axiomatics of Distance-Based Algorithmic Recourse Jenny Hamer Jake Valladares Vignesh Viswanathan Yair Zick 214 2 0 27 Jun 2023
Explainable Predictive Maintenance Sepideh Pashami Sławomir Nowaczyk Yuantao Fan Jakub Jakubowski Nuno Paiva ... Bruno Veloso M. Sayed-Mouchaweh L. Rajaoarisoa Grzegorz J. Nalepa João Gama 184 17 0 08 Jun 2023
GLOBE-CE: A Translation-Based Approach for Global Counterfactual ExplanationsInternational Conference on Machine Learning (ICML), 2023 Dan Ley Saumitra Mishra Daniele Magazzeni LRM 310 23 0 26 May 2023
Achieving Diversity in Counterfactual Explanations: a Review and DiscussionConference on Fairness, Accountability and Transparency (FAccT), 2023 Thibault Laugel Adulam Jeyasothy Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki CML 162 15 0 10 May 2023
counterfactuals: An R Package for Counterfactual Explanation Methods Susanne Dandl Andreas Hofheinz Martin Binder J. Herbinger Giuseppe Casalicchio 259 2 0 13 Apr 2023
CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing FlowsPacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023 Tri Dung Duong Qian Li Guandong Xu OOD 200 7 0 26 Mar 2023
Towards Learning and Explaining Indirect Causal Effects in Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2023 Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 290 1 0 24 Mar 2023
Semi-supervised counterfactual explanations Shravan Kumar Sajja Sumanta Mukherjee Satyam Dwivedi OOD CML 90 2 0 22 Mar 2023