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An Evaluation of the Human-Interpretability of Explanation

31 January 2019

Finale Doshi-Velez

Papers citing "An Evaluation of the Human-Interpretability of Explanation"

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Title
On the notion of missingness for path attribution explainability methods in medical settings: Guiding the selection of medically meaningful baselines Alexander Geiger Lars Wagner Daniel Rueckert Dirk Wilhelm A. Jell OOD BDL MedIm 267 0 0 20 Aug 2025
Never Compromise to Vulnerabilities: A Comprehensive Survey on AI Governance Yuchu Jiang Jian Zhao Yuchen Yuan Tianle Zhang Yao Huang ... Ya Zhang Shuicheng Yan Chi Zhang Z. He Xuelong Li SILM 382 2 0 12 Aug 2025
CASE: Contrastive Activation for Saliency Estimation Dane Williamson Yangfeng Ji Matthew B. Dwyer FAtt AAML 281 0 0 08 Jun 2025
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation Dayeon Ki Kevin Duh Marine Carpuat 170 2 0 30 May 2025
See What I Mean? CUE: A Cognitive Model of Understanding Explanations Tobias Labarta Nhi Hoang Katharina Weitz Wojciech Samek Sebastian Lapuschkin Leander Weber 197 0 0 09 May 2025
Reasoning Models Don't Always Say What They Think Yanda Chen Joe Benton Ansh Radhakrishnan Jonathan Uesato Carson E. Denison ... Vlad Mikulik Samuel R. Bowman Jan Leike Jared Kaplan E. Perez ReLM LRM 378 165 1 08 May 2025
B-cos LM: Efficiently Transforming Pre-trained Language Models for Improved Explainability Yifan Wang Sukrut Rao Ji-Ung Lee Mayank Jobanputra Vera Demberg 167 0 0 18 Feb 2025
Generative Example-Based Explanations: Bridging the Gap between Generative Modeling and Explainability Philipp Vaeth Alexander M. Fruehwald Benjamin Paassen Magda Gregorova GAN 236 1 0 28 Oct 2024
A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning Eura Nofshin Esther Brown Brian Lim Weiwei Pan Finale Doshi-Velez 236 1 0 31 May 2024
Does Your Model Think Like an Engineer? Explainable AI for Bearing Fault Detection with Deep Learning Thomas Decker Michael Lebacher Volker Tresp 97 14 0 19 Oct 2023
Quantifying the Plausibility of Context Reliance in Neural Machine TranslationInternational Conference on Learning Representations (ICLR), 2023 Gabriele Sarti Grzegorz Chrupala Malvina Nissim Arianna Bisazza 242 5 0 02 Oct 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals Greta Warren Markt. Keane Christophe Guéret Eoin Delaney 125 14 0 16 Mar 2023
ASQ-IT: Interactive Explanations for Reinforcement-Learning Agents Yotam Amitai Guy Avni Ofra Amir 232 3 0 24 Jan 2023
Selective Explanations: Leveraging Human Input to Align Explainable AI Vivian Lai Yiming Zhang Chacha Chen Q. V. Liao Chenhao Tan 287 55 0 23 Jan 2023
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations DifferArtificial Intelligence (AI), 2022 Eoin Delaney A. Pakrashi Derek Greene Markt. Keane 210 21 0 16 Dec 2022
The Influence of Explainable Artificial Intelligence: Nudging Behaviour or Boosting Capability? Matija Franklin TDI 149 1 0 05 Oct 2022
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations Mandeep Rathee Thorben Funke Avishek Anand Megha Khosla 139 17 0 28 Jun 2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal Dan Ley Satyapriya Krishna Eshika Saxena Martin Pawelczyk Nari Johnson Isha Puri Marinka Zitnik Himabindu Lakkaraju XAI 386 167 0 22 Jun 2022
Xplique: A Deep Learning Explainability Toolbox Thomas Fel Lucas Hervier David Vigouroux Antonin Poché Justin Plakoo ... Agustin Picard C. Nicodeme Laurent Gardes G. Flandin Thomas Serre 168 40 0 09 Jun 2022
Use-Case-Grounded Simulations for Explanation EvaluationNeural Information Processing Systems (NeurIPS), 2022 Valerie Chen Nari Johnson Nicholay Topin Gregory Plumb Ameet Talwalkar FAtt ELM 174 24 0 05 Jun 2022
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc ExplanationsAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2022 Jessica Dai Sohini Upadhyay Ulrich Aïvodji Stephen H. Bach Himabindu Lakkaraju 209 61 0 15 May 2022
Rethinking Explainability as a Dialogue: A Practitioner's Perspective Himabindu Lakkaraju Dylan Slack Yuxin Chen Chenhao Tan Sameer Singh LRM 197 72 0 03 Feb 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 157 1 0 30 Jan 2022
Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule SetsIEEE Transactions on Visualization and Computer Graphics (TVCG), 2022 Jun Yuan Brian Barr Kyle Overton E. Bertini 117 13 0 19 Jan 2022
More Than Words: Towards Better Quality Interpretations of Text Classifiers Muhammad Bilal Zafar Philipp Schmidt Michele Donini Cédric Archambeau F. Biessmann Sanjiv Ranjan Das K. Kenthapadi FAtt 180 6 0 23 Dec 2021
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies Vivian Lai Chacha Chen Q. V. Liao Alison Smith-Renner Chenhao Tan 229 208 0 21 Dec 2021
LoNLI: An Extensible Framework for Testing Diverse Logical Reasoning Capabilities for NLILanguage Resources and Evaluation (LRE), 2021 Ishan Tarunesh Somak Aditya Monojit Choudhury ELM LRM 131 4 0 04 Dec 2021
Improving Users' Mental Model with Attention-directed Counterfactual Edits Kamran Alipour Arijit Ray Xiaoyu Lin Michael Cogswell J. Schulze Yi Yao Giedrius Burachas OOD 181 11 0 13 Oct 2021
Explaining Reward Functions to Humans for Better Human-Robot Collaboration Lindsay M. Sanneman J. Shah 121 5 0 08 Oct 2021
An Exploration And Validation of Visual Factors in Understanding Classification Rule Sets Jun Yuan O. Nov E. Bertini 179 10 0 19 Sep 2021
Trusting RoBERTa over BERT: Insights from CheckListing the Natural Language Inference Task Ishan Tarunesh Somak Aditya Monojit Choudhury 104 17 0 15 Jul 2021
A Review of Explainable Artificial Intelligence in Manufacturing G. Sofianidis Jože M. Rožanec Dunja Mladenić D. Kyriazis 126 25 0 05 Jul 2021
Learnt Sparsification for Interpretable Graph Neural Networks Mandeep Rathee Zijian Zhang Thorben Funke Megha Khosla Avishek Anand 135 4 0 23 Jun 2021
Abstraction, Validation, and Generalization for Explainable Artificial IntelligenceApplied AI Letters (AA), 2021 Scott Cheng-Hsin Yang Tomas Folke Patrick Shafto 151 6 0 16 May 2021
Visualizing Rule Sets: Exploration and Validation of a Design Space Jun Yuan O. Nov E. Bertini 169 1 0 01 Mar 2021
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and BeyondInformation Fusion (Inf. Fusion), 2021 Guang Yang Qinghao Ye Jun Xia 225 563 0 03 Feb 2021
Evaluating the Interpretability of Generative Models by Interactive ReconstructionInternational Conference on Human Factors in Computing Systems (CHI), 2021 A. Ross Nina Chen Elisa Zhao Hang Elena L. Glassman Finale Doshi-Velez 269 52 0 02 Feb 2021
Explain and Predict, and then Predict AgainWeb Search and Data Mining (WSDM), 2021 Zijian Zhang Koustav Rudra Avishek Anand FAtt 255 57 0 11 Jan 2021
One-shot Policy Elicitation via Semantic Reward Manipulation Aaquib Tabrez Ryan Leonard Bradley Hayes 133 2 0 06 Jan 2021
Challenging common interpretability assumptions in feature attribution explanations Jonathan Dinu Jeffrey P. Bigham J. Z. K. Unaffiliated 216 14 0 04 Dec 2020
Evaluating and Characterizing Human RationalesConference on Empirical Methods in Natural Language Processing (EMNLP), 2020 Samuel Carton Anirudh Rathore Chenhao Tan 169 52 0 09 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 275 182 0 08 Oct 2020
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural NetworksIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020 Thomas Fel David Vigouroux Rémi Cadène Thomas Serre XAI FAtt 309 33 0 07 Sep 2020
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategiesJournal of Biomedical Informatics (JBI), 2020 A. Markus J. Kors P. Rijnbeek 223 560 0 31 Jul 2020
The Impact of Explanations on AI Competency Prediction in VQA Kamran Alipour Arijit Ray Xiaoyu Lin J. Schulze Yi Yao Giedrius Burachas 180 11 0 02 Jul 2020
Does Explainable Artificial Intelligence Improve Human Decision-Making? Y. Alufaisan L. Marusich J. Bakdash Yan Zhou Murat Kantarcioglu XAI 202 115 0 19 Jun 2020
Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making Harini Suresh Natalie Lao Ilaria Liccardi 74 60 0 22 May 2020
Explainable Deep Learning: A Field Guide for the UninitiatedJournal of Artificial Intelligence Research (JAIR), 2020 Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 346 414 0 30 Apr 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data B. Shickel Parisa Rashidi AI4TS 191 21 0 27 Apr 2020
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?Annual Meeting of the Association for Computational Linguistics (ACL), 2020 Alon Jacovi Yoav Goldberg XAI 450 679 0 07 Apr 2020