Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

11 August 2020

Himabindu Lakkaraju

Papers citing "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability"

50 / 97 papers shown

Title
Fixed Point Explainability Emanuele La Malfa Jon Vadillo Marco Molinari Michael Wooldridge 14 0 0 18 May 2025
Display Content, Display Methods and Evaluation Methods of the HCI in Explainable Recommender Systems: A Survey Weiqing Li Yue Xu Yuefeng Li Yinghui Huang 30 0 0 14 May 2025
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning Volkan Bakir Polat Goktas Sureyya Akyuz 57 0 0 26 Apr 2025
Are We Merely Justifying Results ex Post Facto? Quantifying Explanatory Inversion in Post-Hoc Model Explanations Zhen Tan Song Wang Yifan Li Yu Kong Jundong Li Tianlong Chen Huan Liu FAtt 48 0 0 11 Apr 2025
Uncertainty Propagation in XAI: A Comparison of Analytical and Empirical Estimators Teodor Chiaburu Felix Bießmann Frank Haußer 25 0 0 01 Apr 2025
Feature Importance Depends on Properties of the Data: Towards Choosing the Correct Explanations for Your Data and Decision Trees based Models Célia Wafa Ayad Thomas Bonnier Benjamin Bosch Sonali Parbhoo Jesse Read FAtt XAI 105 0 0 11 Feb 2025
An Open API Architecture to Discover the Trustworthy Explanation of Cloud AI Services Zerui Wang Yan Liu Jun Huang 59 1 0 05 Nov 2024
Explainability in AI Based Applications: A Framework for Comparing Different Techniques Arne Grobrugge Nidhi Mishra Johannes Jakubik G. Satzger 107 1 0 28 Oct 2024
Ensured: Explanations for Decreasing the Epistemic Uncertainty in Predictions Helena Lofstrom Tuwe Löfström Johan Hallberg Szabadvary 40 0 0 07 Oct 2024
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Models Sepehr Kamahi Yadollah Yaghoobzadeh 55 0 0 21 Aug 2024
Fooling SHAP with Output Shuffling Attacks Jun Yuan Aritra Dasgupta 40 1 0 12 Aug 2024
From Feature Importance to Natural Language Explanations Using LLMs with RAG Sule Tekkesinoglu Lars Kunze FAtt 39 1 0 30 Jul 2024
Robustness of Explainable Artificial Intelligence in Industrial Process Modelling Benedikt Kantz Clemens Staudinger C. Feilmayr Johannes Wachlmayr Alexander Haberl Stefan Schuster Franz Pernkopf 33 3 0 12 Jul 2024
Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning Jiajun Zhu Siqi Miao Rex Ying Pan Li 45 1 0 30 Jun 2024
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 50 3 0 26 Jun 2024
CAT: Interpretable Concept-based Taylor Additive Models Viet Duong Qiong Wu Zhengyi Zhou Hongjue Zhao Chenxiang Luo Eric Zavesky Huaxiu Yao Huajie Shao FAtt 29 2 0 25 Jun 2024
ProtoS-ViT: Visual foundation models for sparse self-explainable classifications Hugues Turbé Mina Bjelogrlic G. Mengaldo Christian Lovis ViT 28 6 0 14 Jun 2024
Why do explanations fail? A typology and discussion on failures in XAI Clara Bove Thibault Laugel Marie-Jeanne Lesot C. Tijus Marcin Detyniecki 35 2 0 22 May 2024
Evaluating Saliency Explanations in NLP by Crowdsourcing Xiaotian Lu Jiyi Li Zhen Wan Xiaofeng Lin Koh Takeuchi Hisashi Kashima XAI FAtt LRM 34 1 0 17 May 2024
Post-hoc and manifold explanations analysis of facial expression data based on deep learning Yang Xiao 31 0 0 29 Apr 2024
How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps Romy Müller HAI 47 6 0 03 Apr 2024
Segmentation, Classification and Interpretation of Breast Cancer Medical Images using Human-in-the-Loop Machine Learning David Vázquez-Lema E. Mosqueira-Rey Elena Hernández-Pereira Carlos Fernández-Lozano Fernando Seara-Romera Jorge Pombo-Otero LM&MA 38 1 0 29 Mar 2024
Evaluating Explanatory Capabilities of Machine Learning Models in Medical Diagnostics: A Human-in-the-Loop Approach José Bobes-Bascarán E. Mosqueira-Rey Á. Fernández-Leal Elena Hernández-Pereira David Alonso-Ríos V. Moret-Bonillo Israel Figueirido-Arnoso Y. Vidal-Ínsua ELM 29 0 0 28 Mar 2024
Sanity Checks for Explanation Uncertainty Matias Valdenegro-Toro Mihir Mulye FAtt 41 0 0 25 Mar 2024
Uncertainty Quantification for Gradient-based Explanations in Neural Networks Mihir Mulye Matias Valdenegro-Toro UQCV FAtt 43 0 0 25 Mar 2024
QUCE: The Minimisation and Quantification of Path-Based Uncertainty for Generative Counterfactual Explanations J. Duell M. Seisenberger Hsuan-Wei Fu Xiuyi Fan UQCV BDL 42 1 0 27 Feb 2024
Investigating the Impact of Model Instability on Explanations and Uncertainty Sara Vera Marjanović Isabelle Augenstein Christina Lioma AAML 50 0 0 20 Feb 2024
Explaining Probabilistic Models with Distributional Values Luca Franceschi Michele Donini Cédric Archambeau Matthias Seeger FAtt 39 2 0 15 Feb 2024
The Duet of Representations and How Explanations Exacerbate It Charles Wan Rodrigo Belo Leid Zejnilovic Susana Lavado CML FAtt 26 1 0 13 Feb 2024
Advancing Explainable AI Toward Human-Like Intelligence: Forging the Path to Artificial Brain Yongchen Zhou Richard Jiang 26 3 0 07 Feb 2024
Variational Shapley Network: A Probabilistic Approach to Self-Explaining Shapley values with Uncertainty Quantification Mert Ketenci Inigo Urteaga Victor Alfonso Rodriguez Noémie Elhadad A. Perotte FAtt 29 0 0 06 Feb 2024
Understanding Disparities in Post Hoc Machine Learning Explanation Vishwali Mhasawade Salman Rahman Zoe Haskell-Craig R. Chunara 34 4 0 25 Jan 2024
The Distributional Uncertainty of the SHAP score in Explainable Machine Learning Santiago Cifuentes L. Bertossi Nina Pardal S. Abriola Maria Vanina Martinez Miguel Romero TDI FAtt 18 0 0 23 Jan 2024
Towards Modeling Uncertainties of Self-explaining Neural Networks via Conformal Prediction Wei Qian Chenxu Zhao Yangyi Li Fenglong Ma Chao Zhang Mengdi Huai UQCV 52 2 0 03 Jan 2024
Rethinking Robustness of Model Attributions Sandesh Kamath Sankalp Mittal Amit Deshpande Vineeth N. Balasubramanian 32 2 0 16 Dec 2023
Generating Explanations to Understand and Repair Embedding-based Entity Alignment Xiaobin Tian Zequn Sun Wei Hu 28 6 0 08 Dec 2023
Uncertainty in Additive Feature Attribution methods Abhishek Madaan Tanya Chowdhury Neha Rana James Allan Tanmoy Chakraborty 34 0 0 29 Nov 2023
Interpretability is in the eye of the beholder: Human versus artificial classification of image segments generated by humans versus XAI Romy Müller Marius Thoss Julian Ullrich Steffen Seitz Carsten Knoll 26 3 0 21 Nov 2023
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma Max Torop A. Masoomi Davin Hill Kivanc Kose Stratis Ioannidis Jennifer Dy 33 4 0 01 Nov 2023
Refutation of Shapley Values for XAI -- Additional Evidence Xuanxiang Huang Sasha Rubin AAML 34 4 0 30 Sep 2023
A Refutation of Shapley Values for Explainability Xuanxiang Huang Sasha Rubin FAtt 26 3 0 06 Sep 2023
Calibrated Explanations for Regression Tuwe Löfström Helena Lofstrom Ulf Johansson Cecilia Sönströd Rudy Matela XAI FAtt 26 2 0 30 Aug 2023
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution T. Idé Naoki Abe 41 4 0 09 Aug 2023
Confident Feature Ranking Bitya Neuhof Y. Benjamini FAtt 34 3 0 28 Jul 2023
Saliency strikes back: How filtering out high frequencies improves white-box explanations Sabine Muzellec Thomas Fel Victor Boutin Léo Andéol R. V. Rullen Thomas Serre FAtt 32 0 0 18 Jul 2023
Stability Guarantees for Feature Attributions with Multiplicative Smoothing Anton Xue Rajeev Alur Eric Wong 46 5 0 12 Jul 2023
On Formal Feature Attribution and Its Approximation Jinqiang Yu Alexey Ignatiev Peter Stuckey 35 8 0 07 Jul 2023
CLIMAX: An exploration of Classifier-Based Contrastive Explanations Praharsh Nanavati Ranjitha Prasad 42 0 0 02 Jul 2023
Explainability is NOT a Game Sasha Rubin Xuanxiang Huang 28 17 0 27 Jun 2023
Are Good Explainers Secretly Human-in-the-Loop Active Learners? Emma Nguyen Abhishek Ghose 21 1 0 24 Jun 2023