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A Survey Of Methods For Explaining Black Box Models

6 February 2018

Papers citing "A Survey Of Methods For Explaining Black Box Models"

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Title
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 53 13 0 16 Mar 2023
Interpretable Ensembles of Hyper-Rectangles as Base Models A. Konstantinov Lev V. Utkin 106 3 0 15 Mar 2023
Explanation Shift: How Did the Distribution Shift Impact the Model? Carlos Mougan Klaus Broelemann David Masip Gjergji Kasneci Thanassis Thiropanis Steffen Staab FAtt 72 2 0 14 Mar 2023
Beyond Demographic Parity: Redefining Equal Treatment Carlos Mougan Laura State Antonio Ferrara Salvatore Ruggieri Steffen Staab FaML 84 1 0 14 Mar 2023
Efficient Computation of Shap Explanation Scores for Neural Network Classifiers via Knowledge Compilation Leopoldo Bertossi Jorge E. Leon FAtt 114 2 0 11 Mar 2023
Towards Trust of Explainable AI in Thyroid Nodule Diagnosis Hung Truong Thanh Nguyen Van Binh Truong V. Nguyen Quoc Hung Cao Quoc Khanh Nguyen 52 13 0 08 Mar 2023
"How to make them stay?" -- Diverse Counterfactual Explanations of Employee Attrition André Artelt Andreas Gregoriades 86 5 0 08 Mar 2023
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning Jasmina Gajcin Ivana Dusparic CML 43 4 0 08 Mar 2023
Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods Julien Ferry Gabriel Laberge Ulrich Aïvodji 107 5 0 08 Mar 2023
Causal Dependence Plots Joshua R. Loftus Lucius E.J. Bynum Sakina Hansen CML 60 1 0 07 Mar 2023
Learning Human-Compatible Representations for Case-Based Decision Support Han Liu Yizhou Tian Chacha Chen Shi Feng Yuxin Chen Chenhao Tan 63 5 0 06 Mar 2023
NxPlain: Web-based Tool for Discovery of Latent Concepts Fahim Dalvi Nadir Durrani Hassan Sajjad Tamim Jaban Musab Husaini Ummar Abbas 57 1 0 06 Mar 2023
Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence Leopoldo Bertossi XAI CML 88 5 0 06 Mar 2023
A System's Approach Taxonomy for User-Centred XAI: A Survey Ehsan Emamirad Pouya Ghiasnezhad Omran A. Haller S. Gregor 88 1 0 06 Mar 2023
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective Xiwei Xuan Ziquan Deng Hsuan-Tien Lin Z. Kong Kwan-Liu Ma AAML FAtt 61 3 0 01 Mar 2023
Steering Recommendations and Visualising Its Impact: Effects on Adolescents' Trust in E-Learning Platforms Jeroen Ooge L. Dereu K. Verbert LLMSV 34 8 0 28 Feb 2023
Towards Audit Requirements for AI-based Systems in Mobility Applications Devi Alagarswamy Christian Berghoff Vasilios Danos Fabian Langer Thora Markert Georg Schneider Arndt von Twickel Fabian Woitschek 25 1 0 27 Feb 2023
MDF-Net for abnormality detection by fusing X-rays with clinical data Chih-Jou Hsieh Isabel Blanco Nobre Sandra Costa Sousa Chun Ouyang M. Brereton Jacinto C. Nascimento Joaquim A. Jorge Catarina Moreira 54 11 0 26 Feb 2023
Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues Riccardo Albertoni Sara Colantonio Piotr Skrzypczyñski J. Stefanowski 66 10 0 24 Feb 2023
Concept Learning for Interpretable Multi-Agent Reinforcement Learning Renos Zabounidis Joseph Campbell Simon Stepputtis Dana Hughes Katia Sycara 91 17 0 23 Feb 2023
Non-Uniform Interpolation in Integrated Gradients for Low-Latency Explainable-AI Ashwin Bhat A. Raychowdhury 98 4 0 22 Feb 2023
Bridging the Transparency Gap: What Can Explainable AI Learn From the AI Act? Bálint Gyevnár Nick Ferguson Burkhard Schafer 112 18 0 21 Feb 2023
Designerly Understanding: Information Needs for Model Transparency to Support Design Ideation for AI-Powered User Experience Q. V. Liao Hariharan Subramonyam Jennifer Wang Jennifer Wortman Vaughan HAI 86 61 0 21 Feb 2023
Why is the prediction wrong? Towards underfitting case explanation via meta-classification Sheng Zhou P. Blanchart M. Crucianu Marin Ferecatu 121 1 0 20 Feb 2023
Less is More: The Influence of Pruning on the Explainability of CNNs David Weber F. Merkle Pascal Schöttle Stephan Schlögl Martin Nocker FAtt 196 1 0 17 Feb 2023
Competent but Rigid: Identifying the Gap in Empowering AI to Participate Equally in Group Decision-Making Chengbo Zheng Yuheng Wu Chuhan Shi Shuai Ma Jiehui Luo Xiaojuan Ma 90 28 0 17 Feb 2023
The Inadequacy of Shapley Values for Explainability Xuanxiang Huang Sasha Rubin FAtt 105 41 0 16 Feb 2023
Streamlining models with explanations in the learning loop Francesco Lomuscio P. Bajardi Alan Perotti E. Amparore FAtt 82 0 0 15 Feb 2023
Unboxing Tree Ensembles for interpretability: a hierarchical visualization tool and a multivariate optimal re-built tree Giulia Di Teodoro Marta Monaci L. Palagi 64 8 0 15 Feb 2023
A Review of the Role of Causality in Developing Trustworthy AI Systems Niloy Ganguly Dren Fazlija Maryam Badar M. Fisichella Sandipan Sikdar ... Koustav Rudra Manolis Koubarakis Gourab K. Patro W. Z. E. Amri Wolfgang Nejdl CML 89 26 0 14 Feb 2023
Explaining text classifiers through progressive neighborhood approximation with realistic samples Yi Cai Arthur Zimek Eirini Ntoutsi Gerhard Wunder AI4TS 74 0 0 11 Feb 2023
Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication B. Keenan Kacper Sokol 100 7 0 07 Feb 2023
Personalized Interpretable Classification Zengyou He Yifan Tang Yifan Tang Lianyu Hu Yan Liu Yan Liu 90 0 0 06 Feb 2023
Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAI Upol Ehsan Koustuv Saha M. D. Choudhury Mark O. Riedl 106 65 0 01 Feb 2023
Even if Explanations: Prior Work, Desiderata & Benchmarks for Semi-Factual XAI Saugat Aryal Markt. Keane 84 22 0 27 Jan 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges G. Vouros XAI 135 86 0 24 Jan 2023
Selective Explanations: Leveraging Human Input to Align Explainable AI Vivian Lai Yiming Zhang Chacha Chen Q. V. Liao Chenhao Tan 95 45 0 23 Jan 2023
Interpretability in Activation Space Analysis of Transformers: A Focused Survey Soniya Vijayakumar AI4CE 64 4 0 22 Jan 2023
The Shape of Explanations: A Topological Account of Rule-Based Explanations in Machine Learning Brett Mullins FAtt 53 0 0 22 Jan 2023
ExClaim: Explainable Neural Claim Verification Using Rationalization Sai Gurrapu Lifu Huang Feras A. Batarseh AAML 94 9 0 21 Jan 2023
Rationalization for Explainable NLP: A Survey Sai Gurrapu Ajay Kulkarni Lifu Huang Ismini Lourentzou Laura J. Freeman Feras A. Batarseh 110 35 0 21 Jan 2023
Towards Rigorous Understanding of Neural Networks via Semantics-preserving Transformations Maximilian Schlüter Gerrit Nolte Alnis Murtovi Bernhard Steffen 71 6 0 19 Jan 2023
Exemplars and Counterexemplars Explanations for Image Classifiers, Targeting Skin Lesion Labeling C. Metta Riccardo Guidotti Yuan Yin Patrick Gallinari S. Rinzivillo MedIm 59 11 0 18 Jan 2023
Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery Martina Cinquini F. Giannotti Riccardo Guidotti 75 13 0 18 Jan 2023
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations Valerie Chen Q. V. Liao Jennifer Wortman Vaughan Gagan Bansal 151 114 0 18 Jan 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 112 27 0 17 Jan 2023
$Explaining $\mathcal{ELH}$ Concept Descriptions through Counterfactual Reasoning$ Explaining $\mathcal{ELH}$ Concept Descriptions through Counterfactual Reasoning Leonie Nora Sieger Stefan Heindorf Yasir Mahmood Lukas Blübaum A. N. Ngomo 41 0 0 12 Jan 2023
XDQN: Inherently Interpretable DQN through Mimicking Andreas Kontogiannis G. Vouros 109 1 0 08 Jan 2023
Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy C. Dantas Diego Marcos Dino Ienco AAML GAN 35 0 0 04 Jan 2023
Mapping Knowledge Representations to Concepts: A Review and New Perspectives Lars Holmberg P. Davidsson Per Linde 88 2 0 31 Dec 2022