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
Optimizing for Interpretability in Deep Neural Networks with Tree Regularization Mike Wu S. Parbhoo M. C. Hughes Volker Roth Finale Doshi-Velez AI4CE 24 27 0 14 Aug 2019
Towards Explainable AI Planning as a Service Michael Cashmore Anna Collins Benjamin Krarup Senka Krivic Daniele Magazzeni David Smith 16 50 0 14 Aug 2019
Regional Tree Regularization for Interpretability in Black Box Models Mike Wu S. Parbhoo M. C. Hughes R. Kindle Leo Anthony Celi Maurizio Zazzi Volker Roth Finale Doshi-Velez 23 37 0 13 Aug 2019
Measurable Counterfactual Local Explanations for Any Classifier Adam White Artur Garcez FAtt 20 99 0 08 Aug 2019
How model accuracy and explanation fidelity influence user trust A. Papenmeier G. Englebienne C. Seifert FaML 20 108 0 26 Jul 2019
Aggregation in Value-Based Argumentation Frameworks Grzegorz Lisowski S. Doutre Umberto Grandi 14 0 0 22 Jul 2019
User-Interactive Machine Learning Model for Identifying Structural Relationships of Code Features Ankit Gupta 6 0 0 18 Jul 2019
Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting Ana Lucic H. Haned Maarten de Rijke 20 62 0 17 Jul 2019
Mediation Challenges and Socio-Technical Gaps for Explainable Deep Learning Applications R. Brandão J. Carbonera C. D. Souza J. Ferreira Bernardo Gonçalves C. Leitão 24 12 0 16 Jul 2019
Saliency Maps Generation for Automatic Text Summarization David Tuckey Krysia Broda A. Russo FAtt 23 3 0 12 Jul 2019
Explaining Predictions from Tree-based Boosting Ensembles Ana Lucic H. Haned Maarten de Rijke FAtt 9 5 0 04 Jul 2019
Explaining Deep Learning Models with Constrained Adversarial Examples J. Moore Nils Y. Hammerla C. Watkins AAML GAN 16 38 0 25 Jun 2019
Generating Counterfactual and Contrastive Explanations using SHAP Shubham Rathi 29 56 0 21 Jun 2019
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 39 741 0 19 Jun 2019
Trepan Reloaded: A Knowledge-driven Approach to Explaining Artificial Neural Networks R. Confalonieri Tillman Weyde Tarek R. Besold Fermín Moscoso del Prado Martín 30 24 0 19 Jun 2019
Incorporating Priors with Feature Attribution on Text Classification Frederick Liu Besim Avci FAtt FaML 36 120 0 19 Jun 2019
Understanding artificial intelligence ethics and safety David Leslie FaML AI4TS 30 345 0 11 Jun 2019
Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning Noel Codella Michael Hind Karthikeyan N. Ramamurthy Murray Campbell Amit Dhurandhar Kush R. Varshney Dennis L. Wei Aleksandra Mojsilović 17 4 0 05 Jun 2019
A hybrid machine learning framework for analyzing human decision making through learning preferences Mengzhuo Guo Qingpeng Zhang Xiuwu Liao Youhua Chen Daniel Dajun Zeng 33 8 0 04 Jun 2019
Exploring Computational User Models for Agent Policy Summarization Isaac Lage Daphna Lifschitz Finale Doshi-Velez Ofra Amir LLMAG 18 75 0 30 May 2019
Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach Falco J. Bargagli-Stoffi Kristof De-Witte G. Gnecco 24 15 0 29 May 2019
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling Emmanuel Noutahi Dominique Beaini Julien Horwood Sébastien Giguère Prudencio Tossou AI4CE 24 34 0 28 May 2019
Infusing domain knowledge in AI-based "black box" models for better explainability with application in bankruptcy prediction Sheikh Rabiul Islam W. Eberle Sid Bundy S. Ghafoor MLAU 14 23 0 27 May 2019
Explainable Reinforcement Learning Through a Causal Lens Prashan Madumal Tim Miller L. Sonenberg F. Vetere CML 23 355 0 27 May 2019
Explainable Machine Learning for Scientific Insights and Discoveries R. Roscher B. Bohn Marco F. Duarte Jochen Garcke XAI 35 659 0 21 May 2019
Contrastive Fairness in Machine Learning Tapabrata (Rohan) Chakraborty A. Patra Alison Noble FaML 19 8 0 17 May 2019
How Case Based Reasoning Explained Neural Networks: An XAI Survey of Post-Hoc Explanation-by-Example in ANN-CBR Twins Mark T. Keane Eoin M. Kenny 18 82 0 17 May 2019
What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use S. Tonekaboni Shalmali Joshi M. Mccradden Anna Goldenberg 38 383 0 13 May 2019
Minimalistic Explanations: Capturing the Essence of Decisions M. Schuessler Philipp Weiß FAtt 6 5 0 08 May 2019
Explainability in Human-Agent Systems A. Rosenfeld A. Richardson XAI 32 203 0 17 Apr 2019
A Categorisation of Post-hoc Explanations for Predictive Models John Mitros Brian Mac Namee XAI CML 24 0 0 04 Apr 2019
VINE: Visualizing Statistical Interactions in Black Box Models M. Britton FAtt 25 21 0 01 Apr 2019
Expectation-Aware Planning: A Unifying Framework for Synthesizing and Executing Self-Explaining Plans for Human-Aware Planning S. Sreedharan Tathagata Chakraborti Christian Muise S. Kambhampati 22 20 0 18 Mar 2019
Model-Free Model Reconciliation S. Sreedharan Alberto Olmo Hernandez A. Mishra S. Kambhampati 28 33 0 17 Mar 2019
Online Explanation Generation for Human-Robot Teaming Mehrdad Zakershahrak Ze Gong Nikhillesh Sadassivam Yu Zhang 27 11 0 15 Mar 2019
Natural Language Interaction with Explainable AI Models Arjun Reddy Akula S. Todorovic J. Chai Song-Chun Zhu 30 23 0 13 Mar 2019
Physics Enhanced Artificial Intelligence Patrick O'Driscoll Jaehoon Lee Bo Fu 21 3 0 11 Mar 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 37 1,291 0 10 Mar 2019
Explaining Anomalies Detected by Autoencoders Using SHAP Liat Antwarg Ronnie Mindlin Miller Bracha Shapira Lior Rokach FAtt TDI 19 86 0 06 Mar 2019
A Grounded Interaction Protocol for Explainable Artificial Intelligence Prashan Madumal Tim Miller L. Sonenberg F. Vetere 22 96 0 05 Mar 2019
Outlining the Design Space of Explainable Intelligent Systems for Medical Diagnosis Yao Xie Ge Gao Xiang Ánthony' Chen 11 38 0 16 Feb 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI Shane T. Mueller R. Hoffman W. Clancey Abigail Emrey Gary Klein XAI 18 285 0 05 Feb 2019
Learning Decision Trees Recurrently Through Communication Stephan Alaniz Diego Marcos Bernt Schiele Zeynep Akata 30 16 0 05 Feb 2019
Progressive Explanation Generation for Human-robot Teaming Yu Zhang Mehrdad Zakershahrak LRM 25 5 0 02 Feb 2019
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 39 449 0 27 Jan 2019
Explaining Models: An Empirical Study of How Explanations Impact Fairness Judgment Jonathan Dodge Q. V. Liao Yunfeng Zhang Rachel K. E. Bellamy Casey Dugan FaML 16 125 0 23 Jan 2019
Quantifying Interpretability and Trust in Machine Learning Systems Philipp Schmidt F. Biessmann 16 112 0 20 Jan 2019
Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptions Upol Ehsan Pradyumna Tambwekar Larry Chan Brent Harrison Mark O. Riedl 19 237 0 11 Jan 2019
Personalized explanation in machine learning: A conceptualization J. Schneider J. Handali XAI FAtt 22 17 0 03 Jan 2019
Efficient Search for Diverse Coherent Explanations Chris Russell 31 234 0 02 Jan 2019