The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations

1 June 2021

Papers citing "The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations"

21 / 21 papers shown

Title
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 29 0 0 01 May 2025
Are formal and functional linguistic mechanisms dissociated in language models? Michael Hanna Sandro Pezzelle Yonatan Belinkov 45 0 0 14 Mar 2025
A Tale of Two Imperatives: Privacy and Explainability Supriya Manna Niladri Sett 88 0 0 30 Dec 2024
F-Fidelity: A Robust Framework for Faithfulness Evaluation of Explainable AI Xu Zheng Farhad Shirani Zhuomin Chen Chaohao Lin Wei Cheng Wenbo Guo Dongsheng Luo AAML 28 0 0 03 Oct 2024
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Models Sepehr Kamahi Yadollah Yaghoobzadeh 32 0 0 21 Aug 2024
Benchmarking the Attribution Quality of Vision Models Robin Hesse Simone Schaub-Meyer Stefan Roth FAtt 29 3 0 16 Jul 2024
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 44 3 0 26 Jun 2024
Evaluating Explanation Methods for Vision-and-Language Navigation Guanqi Chen Lei Yang Guanhua Chen Jia Pan XAI 21 0 0 10 Oct 2023
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods Fred Zhang Neel Nanda LLMSV 26 96 0 27 Sep 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 32 32 0 11 Aug 2023
CRAFT: Concept Recursive Activation FacTorization for Explainability Thomas Fel Agustin Picard Louis Bethune Thibaut Boissin David Vigouroux Julien Colin Rémi Cadène Thomas Serre 19 102 0 17 Nov 2022
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Zixi Chen Varshini Subhash Marton Havasi Weiwei Pan Finale Doshi-Velez XAI FAtt 27 18 0 10 Nov 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. B. Bruss 30 14 0 12 Jul 2022
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models Liu Zhendong Wenyu Jiang Yan Zhang Chongjun Wang CML 6 0 0 22 Jun 2022
Mediators: Conversational Agents Explaining NLP Model Behavior Nils Feldhus A. Ravichandran Sebastian Möller 25 16 0 13 Jun 2022
A Sea of Words: An In-Depth Analysis of Anchors for Text Data Gianluigi Lopardo F. Precioso Damien Garreau 19 6 0 27 May 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection Esma Balkir I. Nejadgholi Kathleen C. Fraser S. Kiritchenko FAtt 25 27 0 06 May 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 18 41 0 15 Feb 2022
Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models? Thang M. Pham Trung H. Bui Long Mai Anh Totti Nguyen 21 7 0 22 Oct 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations N. Jethani Mukund Sudarshan Yindalon Aphinyanagphongs Rajesh Ranganath FAtt 78 70 0 02 Mar 2021
Feature Importance Ranking for Deep Learning Maksymilian Wojtas Ke Chen 129 116 0 18 Oct 2020