Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

6 November 2019

Himabindu Lakkaraju

Papers citing "Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods"

50 / 133 papers shown

Title
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Logic-Based Explainability in Machine Learning Sasha Rubin LRM XAI 50 39 0 24 Oct 2022
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification Adrien Bennetot Gianni Franchi Javier Del Ser Raja Chatila Natalia Díaz Rodríguez AAML 32 29 0 26 Sep 2022
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making Jakob Schoeffer Maria De-Arteaga Niklas Kuehl FaML 45 46 0 23 Sep 2022
EMaP: Explainable AI with Manifold-based Perturbations Minh Nhat Vu Huy Mai My T. Thai AAML 35 2 0 18 Sep 2022
Macroeconomic Predictions using Payments Data and Machine Learning James T. E. Chapman Ajit Desai 16 15 0 02 Sep 2022
Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research Zhibo Zhang H. A. Hamadi Ernesto Damiani C. Yeun Fatma Taher AAML 32 148 0 31 Aug 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
Explainable AI for tailored electricity consumption feedback -- an experimental evaluation of visualizations Jacqueline Wastensteiner T. Weiß Felix Haag K. Hopf 25 11 0 24 Aug 2022
Augmented cross-selling through explainable AI -- a case from energy retailing Felix Haag K. Hopf Pedro Menelau Vasconcelos Thorsten Staake 26 4 0 24 Aug 2022
Review of Natural Language Processing in Pharmacology D. Trajanov Vangel Trajkovski Makedonka Dimitrieva Jovana Dobreva Milos Jovanovik Matej Klemen Alevs vZagar Marko Robnik-vSikonja LM&MA 23 7 0 22 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
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence Isha Hameed Samuel Sharpe Daniel Barcklow Justin Au-yeung Sahil Verma Jocelyn Huang Brian Barr C. Bayan Bruss 35 14 0 12 Jul 2022
On Computing Relevant Features for Explaining NBCs Yacine Izza Sasha Rubin 36 5 0 11 Jul 2022
"Explanation" is Not a Technical Term: The Problem of Ambiguity in XAI Leilani H. Gilpin Andrew R. Paley M. A. Alam Sarah Spurlock Kristian J. Hammond XAI 26 6 0 27 Jun 2022
Eliminating The Impossible, Whatever Remains Must Be True Jinqiang Yu Alexey Ignatiev Peter J. Stuckey Nina Narodytska Sasha Rubin 19 23 0 20 Jun 2022
Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets Sreejita Ghosh E. Baranowski Michael Biehl W. Arlt Peter Tiño the United Kingdom Utrecht University 23 6 0 04 Jun 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 47 18 0 31 May 2022
Fool SHAP with Stealthily Biased Sampling Gabriel Laberge Ulrich Aïvodji Satoshi Hara M. Marchand Foutse Khomh MLAU AAML FAtt 10 2 0 30 May 2022
Unfooling Perturbation-Based Post Hoc Explainers Zachariah Carmichael Walter J. Scheirer AAML 60 14 0 29 May 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 32 46 0 27 May 2022
Prototype Based Classification from Hierarchy to Fairness Mycal Tucker J. Shah FaML 16 6 0 27 May 2022
The Solvability of Interpretability Evaluation Metrics Yilun Zhou J. Shah 70 8 0 18 May 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 30 26 0 16 May 2022
Can Rationalization Improve Robustness? Howard Chen Jacqueline He Karthik Narasimhan Danqi Chen AAML 23 40 0 25 Apr 2022
Backdooring Explainable Machine Learning Maximilian Noppel Lukas Peter Christian Wressnegger AAML 16 5 0 20 Apr 2022
Marrying Fairness and Explainability in Supervised Learning Przemyslaw A. Grabowicz Nicholas Perello Aarshee Mishra FaML 46 43 0 06 Apr 2022
Interpretation of Black Box NLP Models: A Survey Shivani Choudhary N. Chatterjee S. K. Saha FAtt 34 10 0 31 Mar 2022
Robustness and Usefulness in AI Explanation Methods Erick Galinkin FAtt 28 1 0 07 Mar 2022
Towards a Responsible AI Development Lifecycle: Lessons From Information Security Erick Galinkin SILM 19 6 0 06 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
Margin-distancing for safe model explanation Tom Yan Chicheng Zhang 28 3 0 23 Feb 2022
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners K. Ramamurthy Amit Dhurandhar Dennis L. Wei Zaid Bin Tariq FAtt 38 3 0 02 Feb 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts Sebastian Bordt Michèle Finck Eric Raidl U. V. Luxburg AILaw 39 77 0 25 Jan 2022
GPEX, A Framework For Interpreting Artificial Neural Networks Amir Akbarnejad G. Bigras Nilanjan Ray 47 4 0 18 Dec 2021
LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations Weronika Hryniewska Adrianna Grudzieñ P. Biecek FAtt 53 3 0 15 Nov 2021
Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities Waddah Saeed C. Omlin XAI 36 414 0 11 Nov 2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis Thomas Fel Rémi Cadène Mathieu Chalvidal Matthieu Cord David Vigouroux Thomas Serre MLAU FAtt AAML 114 58 0 07 Nov 2021
Designing Inherently Interpretable Machine Learning Models Agus Sudjianto Aijun Zhang FaML 13 31 0 02 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations Saumitra Mishra Sanghamitra Dutta Jason Long Daniele Magazzeni AAML 14 58 0 30 Oct 2021
Unpacking the Black Box: Regulating Algorithmic Decisions Laura Blattner Scott Nelson Jann Spiess MLAU FaML 28 19 0 05 Oct 2021
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications Dongqi Han Zhiliang Wang Wenqi Chen Ying Zhong Su Wang Han Zhang Jiahai Yang Xingang Shi Xia Yin AAML 24 76 0 23 Sep 2021
Learning Predictive and Interpretable Timeseries Summaries from ICU Data Nari Johnson S. Parbhoo A. Ross Finale Doshi-Velez AI4TS 27 7 0 22 Sep 2021
Attributing Fair Decisions with Attention Interventions Ninareh Mehrabi Umang Gupta Fred Morstatter Greg Ver Steeg Aram Galstyan 32 21 0 08 Sep 2021
Model Explanations via the Axiomatic Causal Lens Gagan Biradar Vignesh Viswanathan Yair Zick XAI CML 25 1 0 08 Sep 2021
On the Veracity of Local, Model-agnostic Explanations in Audio Classification: Targeted Investigations with Adversarial Examples Verena Praher Katharina Prinz A. Flexer Gerhard Widmer AAML FAtt 11 9 0 19 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
What will it take to generate fairness-preserving explanations? Jessica Dai Sohini Upadhyay Stephen H. Bach Himabindu Lakkaraju FAtt FaML 15 14 0 24 Jun 2021
On Locality of Local Explanation Models Sahra Ghalebikesabi Lucile Ter-Minassian Karla Diaz-Ordaz Chris Holmes FedML FAtt 26 39 0 24 Jun 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White W. Neiswanger 37 65 0 23 Jun 2021