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Explanation in Artificial Intelligence: Insights from the Social Sciences

22 June 2017

Papers citing "Explanation in Artificial Intelligence: Insights from the Social Sciences"

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Title
Explainable Reinforcement Learning: A Survey Erika Puiutta Eric M. S. P. Veith XAI 336 279 0 13 May 2020
XEM: An Explainable-by-Design Ensemble Method for Multivariate Time Series Classification Kevin Fauvel Elisa Fromont Véronique Masson P. Faverdin Alexandre Termier AI4TS 341 50 0 07 May 2020
Towards the Role of Theory of Mind in Explanation Maayan Shvo Toryn Q. Klassen Sheila A. McIlraith 142 29 0 06 May 2020
An Investigation of COVID-19 Spreading Factors with Explainable AI Techniques Xiuyi Fan Siyuan Liu Jiarong Chen T. Henderson 96 7 0 05 May 2020
A multi-component framework for the analysis and design of explainable artificial intelligenceMachine Learning and Knowledge Extraction (MLKE), 2020 S. Atakishiyev H. Babiker Nawshad Farruque R. Goebel1 Myeongjung Kima M. H. Motallebi J. Rabelo T. Syed O. R. Zaïane 146 43 0 05 May 2020
Robotic Self-Assessment of Competence Gertjan J. Burghouts A. Huizing Mark Antonius Neerincx 93 7 0 04 May 2020
To Test Machine Comprehension, Start by Defining ComprehensionAnnual Meeting of the Association for Computational Linguistics (ACL), 2020 Jesse Dunietz Greg Burnham Akash Bharadwaj Owen Rambow Jennifer Chu-Carroll D. Ferrucci FaML 195 65 0 04 May 2020
Autoencoders for strategic decision supportDecision Support Systems (DSS), 2020 Sam Verboven Jeroen Berrevoets Chris Wuytens Bart Baesens Wouter Verbeke 65 10 0 03 May 2020
Rationalizing Medical Relation Prediction from Corpus-level StatisticsAnnual Meeting of the Association for Computational Linguistics (ACL), 2020 Zhen Wang Jennifer A Lee Simon M. Lin Huan Sun OOD 65 4 0 02 May 2020
The Grammar of Interactive Explanatory Model AnalysisData mining and knowledge discovery (DMKD), 2020 Hubert Baniecki Dariusz Parzych P. Biecek 239 53 0 01 May 2020
Hide-and-Seek: A Template for Explainable AI Thanos Tagaris A. Stafylopatis 100 6 0 30 Apr 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 354 415 0 30 Apr 2020
The Explanation Game: Towards Prediction Explainability through Sparse Communication Marcos Vinícius Treviso André F. T. Martins FAtt 169 3 0 28 Apr 2020
A Disentangling Invertible Interpretation Network for Explaining Latent RepresentationsComputer Vision and Pattern Recognition (CVPR), 2020 Patrick Esser Robin Rombach Bjorn Ommer 180 91 0 27 Apr 2020
Tradeoff-Focused Contrastive Explanation for MDP PlanningIEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2020 Roykrong Sukkerd R. Simmons David Garlan 178 28 0 27 Apr 2020
Why an Android App is Classified as Malware? Towards Malware Classification Interpretation Bozhi Wu Sen Chen Cuiyun Gao Lingling Fan Yang Liu W. Wen Michael R. Lyu 196 66 0 24 Apr 2020
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs Sungsoo Ray Hong Jessica Hullman E. Bertini HAI 235 218 0 23 Apr 2020
Explainable Image Classification with Evidence Counterfactual T. Vermeire David Martens FAtt 73 0 0 16 Apr 2020
Order Matters: Generating Progressive Explanations for Planning Tasks in Human-Robot TeamingIEEE International Conference on Robotics and Automation (ICRA), 2020 Mehrdad Zakershahrak Shashank Rao Marpally Akshay Sharma Ze Gong Yu Zhang LRM 192 8 0 16 Apr 2020
Improved Code Summarization via a Graph Neural NetworkIEEE International Conference on Program Comprehension (ICPC), 2020 Alexander LeClair S. Haque Lingfei Wu Collin McMillan 170 304 0 06 Apr 2020
Improving Confidence in the Estimation of Values and Norms Luciano Cavalcante Siebert Rijk Mercuur Virginia Dignum J. van den Hoven Catholijn M. Jonker 78 0 0 02 Apr 2020
Applying Transparency in Artificial Intelligence based Personalization SystemsUser Modeling, Adaptation, and Personalization (UMAP), 2020 Laura Schelenz A. Segal Y. Gal 171 13 0 02 Apr 2020
Unification-based Reconstruction of Multi-hop Explanations for Science Questions Marco Valentino Mokanarangan Thayaparan André Freitas 179 8 0 31 Mar 2020
Artificial Intelligence for EU Decision-Making. Effects on Citizens Perceptions of Input, Throughput and Output Legitimacy C. Starke Marco Luenich 72 5 0 25 Mar 2020
TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications Kaiping Zheng Shaofeng Cai H. Chua Wei Wang K. Ngiam Beng Chin Ooi AI4TS 126 27 0 24 Mar 2020
Towards Explainability of Machine Learning Models in Insurance Pricing Kevin Kuo Danielle L. Lupton 161 13 0 24 Mar 2020
Interpretable machine learning models: a physics-based view Ion Matei Johan de Kleer C. Somarakis R. Rai John S. Baras PINN AI4CE 60 1 0 22 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves ExplainabilityEuropean Conference on Computer Vision (ECCV), 2020 Maximilian Augustin Alexander Meinke Matthias Hein OOD 310 107 0 20 Mar 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 347 87 0 17 Mar 2020
Directions for Explainable Knowledge-Enabled Systems Shruthi Chari Daniel Gruen Oshani Seneviratne D. McGuinness XAI 183 35 0 17 Mar 2020
Foundations of Explainable Knowledge-Enabled Systems Shruthi Chari Daniel Gruen Oshani Seneviratne D. McGuinness 177 30 0 17 Mar 2020
Towards Transparent Robotic Planning via Contrastive ExplanationsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2020 Shenghui Chen Kayla Boggess Lu Feng 111 11 0 16 Mar 2020
Explainable Agents Through Social Cues: A Review Sebastian Wallkötter Silvia Tulli Ginevra Castellano Ana Paiva Mohamed Chetouani 173 13 0 11 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and EvaluationSIGKDD Explorations (SIGKDD Explor.), 2020 Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 236 240 0 09 Mar 2020
ViCE: Visual Counterfactual Explanations for Machine Learning ModelsInternational Conference on Intelligent User Interfaces (IUI), 2020 Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML 179 102 0 05 Mar 2020
AI-Mediated Exchange Theory Xiao Ma Taylor W. Brown 60 13 0 04 Mar 2020
EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic Analysis Andrea Morichetta P. Casas Marco Mellia 91 67 0 03 Mar 2020
Evidence-based explanation to promote fairness in AI systems J. Ferreira Mateus de Souza Monteiro FaML 101 5 0 03 Mar 2020
A general framework for scientifically inspired explanations in AI David Tuckey A. Russo Krysia Broda 101 0 0 02 Mar 2020
Do ML Experts Discuss Explainability for AI Systems? A discussion case in the industry for a domain-specific solution J. Ferreira Mateus de Souza Monteiro 126 8 0 27 Feb 2020
The Emerging Landscape of Explainable AI Planning and Decision MakingInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 Tathagata Chakraborti S. Sreedharan S. Kambhampati 175 122 0 26 Feb 2020
Problems with Shapley-value-based explanations as feature importance measuresInternational Conference on Machine Learning (ICML), 2020 Indra Elizabeth Kumar Suresh Venkatasubramanian C. Scheidegger Sorelle A. Friedler TDI FAtt 312 429 0 25 Feb 2020
The Pragmatic Turn in Explainable Artificial Intelligence (XAI)Minds and Machines (MM), 2019 Andrés Páez 165 215 0 22 Feb 2020
An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics Catarina Moreira Prerna Agarwal Chun Ouyang P. Bruza Andreas Wichert 109 5 0 21 Feb 2020
Interpretability of machine learning based prediction models in healthcare Gregor Stiglic Primož Kocbek Nino Fijačko Marinka Zitnik K. Verbert Leona Cilar AI4CE 252 463 0 20 Feb 2020
Algorithmic Recourse: from Counterfactual Explanations to InterventionsConference on Fairness, Accountability and Transparency (FAccT), 2020 Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 419 389 0 14 Feb 2020
A Hierarchy of Limitations in Machine Learning M. Malik 159 66 0 12 Feb 2020
What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations Michal Kuzba P. Biecek HAI 122 25 0 07 Feb 2020
`Why didn't you allocate this task to them?' Negotiation-Aware Explicable Task Allocation and Contrastive Explanation Generation Z. Zahedi Sailik Sengupta Subbarao Kambhampati 225 3 0 05 Feb 2020
Human-centered Explainable AI: Towards a Reflective Sociotechnical ApproachInteracción (HCI International), 2020 Upol Ehsan Mark O. Riedl 214 254 0 04 Feb 2020