Explaining Explanations in AI

4 November 2018

Papers citing "Explaining Explanations in AI"

29 / 79 papers shown

Title
Expanding Explainability: Towards Social Transparency in AI systems Upol Ehsan Q. V. Liao Michael J. Muller Mark O. Riedl Justin D. Weisz 43 394 0 12 Jan 2021
Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning Stefanos Tsimenidis 25 12 0 22 Dec 2020
Transformer Interpretability Beyond Attention Visualization Hila Chefer Shir Gur Lior Wolf 45 645 0 17 Dec 2020
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models Tom Heskes E. Sijben I. G. Bucur Tom Claassen FAtt TDI 14 151 0 03 Nov 2020
Shapley Flow: A Graph-based Approach to Interpreting Model Predictions Jiaxuan Wang Jenna Wiens Scott M. Lundberg FAtt 25 88 0 27 Oct 2020
Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable? Manas Gaur Keyur Faldu A. Sheth 37 113 0 16 Oct 2020
A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations Andrea Ferrario M. Loi 25 5 0 09 Oct 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 19 89 0 28 Sep 2020
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring Nijat Mehdiyev Peter Fettke AI4TS 25 55 0 04 Sep 2020
Ethical behavior in humans and machines -- Evaluating training data quality for beneficial machine learning Thilo Hagendorff 21 26 0 26 Aug 2020
Survey of XAI in digital pathology Milda Pocevičiūtė Gabriel Eilertsen Claes Lundström 14 56 0 14 Aug 2020
Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis Ming Fan Wenying Wei Xiaofei Xie Yang Liu X. Guan Ting Liu FAtt AAML 27 36 0 13 Aug 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay Sasha Rubin Thomas Gerspacher Martin C. Cooper Alexey Ignatiev Nina Narodytska FAtt 30 59 0 13 Aug 2020
Who is this Explanation for? Human Intelligence and Knowledge Graphs for eXplainable AI I. Celino 12 5 0 27 May 2020
Reliable Local Explanations for Machine Listening Saumitra Mishra Emmanouil Benetos Bob L. T. Sturm S. Dixon AAML FAtt 12 20 0 15 May 2020
Directions for Explainable Knowledge-Enabled Systems Shruthi Chari Daniel Gruen Oshani Seneviratne D. McGuinness XAI 21 32 0 17 Mar 2020
Foundations of Explainable Knowledge-Enabled Systems Shruthi Chari Daniel Gruen Oshani Seneviratne D. McGuinness 44 28 0 17 Mar 2020
Towards Transparent Robotic Planning via Contrastive Explanations Shenghui Chen Kayla Boggess Lu Feng 20 9 0 16 Mar 2020
The Pragmatic Turn in Explainable Artificial Intelligence (XAI) Andrés Páez 27 191 0 22 Feb 2020
Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning Akanksha Atrey Kaleigh Clary David D. Jensen FAtt LRM 30 90 0 09 Dec 2019
"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning M. Sendak M. C. Elish M. Gao Joseph D. Futoma W. Ratliff M. Nichols A. Bedoya S. Balu Cara O'Brien HAI 19 167 0 19 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 35 805 0 06 Nov 2019
Global Aggregations of Local Explanations for Black Box models I. V. D. Linden H. Haned Evangelos Kanoulas FAtt 27 63 0 05 Jul 2019
Generating Counterfactual and Contrastive Explanations using SHAP Shubham Rathi 29 56 0 21 Jun 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 15 82 0 17 May 2019
The Ethics of AI Ethics -- An Evaluation of Guidelines Thilo Hagendorff AI4TS 28 1,157 0 28 Feb 2019
Efficient Search for Diverse Coherent Explanations Chris Russell 31 234 0 02 Jan 2019
Complementary reinforcement learning towards explainable agents J. H. Lee 27 12 0 01 Jan 2019
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017