The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations

22 July 2019

Papers citing "The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations"

38 / 38 papers shown

Title
When Counterfactual Reasoning Fails: Chaos and Real-World Complexity Yahya Aalaila Gerrit Großmann Sumantrak Mukherjee Jonas Wahl Sebastian Vollmer CML LRM 64 0 0 31 Mar 2025
Re-Imagining Multimodal Instruction Tuning: A Representation View Yiyang Liu James Liang Ruixiang Tang Yugyung Lee Majid Rabbani ... Raghuveer M. Rao Lifu Huang Dongfang Liu Qifan Wang Cheng Han 135 0 0 02 Mar 2025
Concept Layers: Enhancing Interpretability and Intervenability via LLM Conceptualization Or Raphael Bidusa Shaul Markovitch 61 0 0 20 Feb 2025
CHILLI: A data context-aware perturbation method for XAI Saif Anwar Nathan Griffiths A. Bhalerao T. Popham 44 0 0 10 Jul 2024
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 29 0 0 20 Nov 2023
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations Chiyu Ma Brandon Zhao Chaofan Chen Cynthia Rudin 26 26 0 28 Oct 2023
Towards Faithful Neural Network Intrinsic Interpretation with Shapley Additive Self-Attribution Ying Sun Hengshu Zhu Huixia Xiong TDI FAtt MILM 25 1 0 27 Sep 2023
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations Emanuele Albini Shubham Sharma Saumitra Mishra Danial Dervovic Daniele Magazzeni FAtt 46 2 0 13 Jul 2023
Interpretable (not just posthoc-explainable) heterogeneous survivor bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions Hongjing Xia Joshua C. Chang S. Nowak Sonya Mahajan R. Mahajan Ted L. Chang Carson C. Chow 38 1 0 19 Apr 2023
An Interpretable Loan Credit Evaluation Method Based on Rule Representation Learner Zi-yu Chen Xiaomeng Wang Yuanjiang Huang Tao Jia 33 1 0 03 Apr 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson Amir Dezfouli Robert Kohn 31 4 0 02 Feb 2023
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ Eoin Delaney A. Pakrashi Derek Greene Markt. Keane 35 15 0 16 Dec 2022
Mixture of Decision Trees for Interpretable Machine Learning Simeon Brüggenjürgen Nina Schaaf P. Kerschke Marco F. Huber MoE 14 0 0 26 Nov 2022
Decomposing Counterfactual Explanations for Consequential Decision Making Martin Pawelczyk Lea Tiyavorabun Gjergji Kasneci CML 21 1 0 03 Nov 2022
Improvement-Focused Causal Recourse (ICR) Gunnar Konig Timo Freiesleben Moritz Grosse-Wentrup CML 34 15 0 27 Oct 2022
Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death Joshua C. Chang Ted L. Chang Carson C. Chow R. Mahajan Sonya Mahajan Joe Maisog Shashaank Vattikuti Hongjing Xia FAtt OOD 37 0 0 28 Aug 2022
Equivariant and Invariant Grounding for Video Question Answering Yicong Li Xiang Wang Junbin Xiao Tat-Seng Chua 20 25 0 26 Jul 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 44 18 0 31 May 2022
Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries Haekyu Park Seongmin Lee Benjamin Hoover Austin P. Wright Omar Shaikh Rahul Duggal Nilaksh Das Kevin Li Judy Hoffman Duen Horng Chau 24 2 0 30 Mar 2022
Sensing accident-prone features in urban scenes for proactive driving and accident prevention Sumit Mishra Praveenbalaji Rajendran L. Vecchietti Dongsoo Har 19 13 0 25 Feb 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 26 36 0 22 Jan 2022
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation M. Temraz Markt. Keane 21 42 0 05 Nov 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 26 49 0 27 Oct 2021
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies F. Xie Han Yuan Yilin Ning M. Ong Mengling Feng W. Hsu B. Chakraborty Nan Liu 27 83 0 21 Jul 2021
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations Bodhisattwa Prasad Majumder Oana-Maria Camburu Thomas Lukasiewicz Julian McAuley 25 35 0 25 Jun 2021
Characterizing the risk of fairwashing Ulrich Aïvodji Hiromi Arai Sébastien Gambs Satoshi Hara 23 27 0 14 Jun 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 47 176 0 07 Mar 2021
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning Jiaheng Xie Xinyu Liu HAI 31 10 0 21 Dec 2020
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 80 262 0 03 Dec 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 20 397 0 19 Oct 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 19 89 0 28 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 38 62 0 11 Sep 2020
Model extraction from counterfactual explanations Ulrich Aïvodji Alexandre Bolot Sébastien Gambs MIACV MLAU 30 51 0 03 Sep 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 30 625 0 01 Jul 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 25 85 0 23 Jun 2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition Mahsan Nourani Chiradeep Roy Tahrima Rahman Eric D. Ragan Nicholas Ruozzi Vibhav Gogate AAML 15 17 0 05 May 2020
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches Kacper Sokol Peter A. Flach XAI 17 299 0 11 Dec 2019