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
Do Natural Language Explanations Represent Valid Logical Arguments? Verifying Entailment in Explainable NLI Gold Standards Marco Valentino Ian Pratt-Hartman André Freitas XAI LRM 31 12 0 05 May 2021
Explanation-Based Human Debugging of NLP Models: A Survey Piyawat Lertvittayakumjorn Francesca Toni LRM 47 79 0 30 Apr 2021
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation Markt. Keane Eoin M. Kenny M. Temraz Derek Greene Barry Smyth 19 5 0 29 Apr 2021
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence David Alvarez-Melis Harmanpreet Kaur Hal Daumé Hanna M. Wallach Jennifer Wortman Vaughan FAtt 56 28 0 27 Apr 2021
TrustyAI Explainability Toolkit Rob Geada Tommaso Teofili Rui Vieira Rebecca Whitworth Daniele Zonca 16 2 0 26 Apr 2021
Axes for Sociotechnical Inquiry in AI Research Sarah Dean T. Gilbert Nathan Lambert Tom Zick 41 12 0 26 Apr 2021
Rich Semantics Improve Few-shot Learning Mohamed Afham Salman Khan Muhammad Haris Khan Muzammal Naseer Fahad Shahbaz Khan VLM 37 24 0 26 Apr 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 34 83 0 26 Apr 2021
A Picture is Worth a Collaboration: Accumulating Design Knowledge for Computer-Vision-based Hybrid Intelligence Systems Patrick Zschech J. Walk Kai Heinrich Michael Vossing Niklas Kühl 23 4 0 23 Apr 2021
A Novel Interaction-based Methodology Towards Explainable AI with Better Understanding of Pneumonia Chest X-ray Images S. Lo Yiqiao Yin 30 8 0 19 Apr 2021
Interpretability in deep learning for finance: a case study for the Heston model D. Brigo Xiaoshan Huang A. Pallavicini Haitz Sáez de Ocáriz Borde FAtt 22 8 0 19 Apr 2021
GraphSVX: Shapley Value Explanations for Graph Neural Networks Alexandre Duval Fragkiskos D. Malliaros FAtt 22 86 0 18 Apr 2021
Explaining Answers with Entailment Trees Bhavana Dalvi Peter Alexander Jansen Oyvind Tafjord Zhengnan Xie Hannah Smith Leighanna Pipatanangkura Peter Clark ReLM FAtt LRM 248 185 0 17 Apr 2021
LEx: A Framework for Operationalising Layers of Machine Learning Explanations Ronal Singh Upol Ehsan M. Cheong Mark O. Riedl Tim Miller 32 3 0 15 Apr 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations Dieter Brughmans Pieter Leyman David Martens 40 64 0 15 Apr 2021
Machine learning and deep learning Christian Janiesch Patrick Zschech Kai Heinrich 26 1,170 0 12 Apr 2021
Enhancing Deep Neural Network Saliency Visualizations with Gradual Extrapolation Tomasz Szandała FAtt 24 4 0 11 Apr 2021
Connecting Attributions and QA Model Behavior on Realistic Counterfactuals Xi Ye Rohan Nair Greg Durrett 24 24 0 09 Apr 2021
Individual Explanations in Machine Learning Models: A Survey for Practitioners Alfredo Carrillo Luis F. Cantú Alejandro Noriega FaML 24 15 0 09 Apr 2021
Question-Driven Design Process for Explainable AI User Experiences Q. V. Liao Milena Pribić Jaesik Han Sarah Miller Daby M. Sow 20 52 0 08 Apr 2021
Towards a Rigorous Evaluation of Explainability for Multivariate Time Series Rohit Saluja A. Malhi Samanta Knapic Kary Främling C. Cavdar XAI AI4TS 23 19 0 06 Apr 2021
Measuring Linguistic Diversity During COVID-19 Artaches Ambartsoumian F. Popowich Benjamin Adams 19 35 0 03 Apr 2021
Reconciling the Discrete-Continuous Divide: Towards a Mathematical Theory of Sparse Communication André F. T. Martins 35 1 0 01 Apr 2021
Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainability Pushkar Mishra H. Yannakoudakis Ekaterina Shutova 19 7 0 31 Mar 2021
Anomaly-Based Intrusion Detection by Machine Learning: A Case Study on Probing Attacks to an Institutional Network E. Tufan C. Tezcan Cengiz Acartürk 26 29 0 31 Mar 2021
Contrastive Explanations of Plans Through Model Restrictions Benjamin Krarup Senka Krivic Daniele Magazzeni D. Long Michael Cashmore David E. Smith 27 32 0 29 Mar 2021
Situated Case Studies for a Human-Centered Design of Explanation User Interfaces Claudia Muller-Birn Katrin Glinka Peter Sorries Michael Tebbe S. Michl 19 2 0 29 Mar 2021
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice David S. Watson Limor Gultchin Ankur Taly Luciano Floridi 22 63 0 27 Mar 2021
Generating and Evaluating Explanations of Attended and Error-Inducing Input Regions for VQA Models Arijit Ray Michael Cogswell Xiaoyu Lin Kamran Alipour Ajay Divakaran Yi Yao Giedrius Burachas FAtt 13 4 0 26 Mar 2021
Towards interpretability of Mixtures of Hidden Markov Models Negar Safinianaini Henrik Bostrom 11 2 0 23 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 30 105 0 22 Mar 2021
Interpreting Deep Learning Models with Marginal Attribution by Conditioning on Quantiles M. Merz Ronald Richman A. Tsanakas M. Wüthrich FAtt 17 11 0 22 Mar 2021
Trustworthy Transparency by Design Valentin Zieglmeier A. Pretschner 18 16 0 19 Mar 2021
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond Xuhong Li Haoyi Xiong Xingjian Li Xuanyu Wu Xiao Zhang Ji Liu Jiang Bian Dejing Dou AAML FaML XAI HAI 28 318 0 19 Mar 2021
XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanations Eunji Kim Siwon Kim Minji Seo Sungroh Yoon ViT FAtt 24 113 0 19 Mar 2021
Integrated Decision and Control: Towards Interpretable and Computationally Efficient Driving Intelligence Yang Guan Yangang Ren Qi Sun Shengbo Eben Li Haitong Ma Jingliang Duan Yifan Dai B. Cheng 18 66 0 18 Mar 2021
Interpretability of a Deep Learning Model in the Application of Cardiac MRI Segmentation with an ACDC Challenge Dataset Adrianna Janik J. Dodd Georgiana Ifrim Kris Sankaran Kathleen M. Curran 33 26 0 15 Mar 2021
A Study of Automatic Metrics for the Evaluation of Natural Language Explanations Miruna Clinciu Arash Eshghi H. Hastie 56 54 0 15 Mar 2021
Explanations in Autonomous Driving: A Survey Daniel Omeiza Helena Webb Marina Jirotka Lars Kunze 11 214 0 09 Mar 2021
A Comparative Approach to Explainable Artificial Intelligence Methods in Application to High-Dimensional Electronic Health Records: Examining the Usability of XAI J. Duell 17 2 0 08 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 52 176 0 07 Mar 2021
Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction Aniruddh Raghu John Guttag K. Young E. Pomerantsev Adrian Dalca Collin M. Stultz 13 9 0 04 Mar 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 49 95 0 02 Mar 2021
Interpretable Artificial Intelligence through the Lens of Feature Interaction Michael Tsang James Enouen Yan Liu FAtt 19 7 0 01 Mar 2021
Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence Atoosa Kasirzadeh 40 24 0 01 Mar 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 32 146 0 26 Feb 2021
Benchmarking and Survey of Explanation Methods for Black Box Models F. Bodria F. Giannotti Riccardo Guidotti Francesca Naretto D. Pedreschi S. Rinzivillo XAI 38 221 0 25 Feb 2021
A Local Method for Identifying Causal Relations under Markov Equivalence Zhuangyan Fang Yue Liu Z. Geng Shengyu Zhu Yangbo He CML 30 13 0 25 Feb 2021
Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing Sarah Wiegreffe Ana Marasović XAI 24 141 0 24 Feb 2021
Artificial Intelligence as an Anti-Corruption Tool (AI-ACT) -- Potentials and Pitfalls for Top-down and Bottom-up Approaches N. Köbis C. Starke Iyad Rahwan 14 11 0 23 Feb 2021