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
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
Contrastive Counterfactual Visual Explanations With Overdetermination Adam White K. Ngan James Phelan Saman Sadeghi Afgeh Kevin Ryan C. Reyes-Aldasoro Artur Garcez 29 8 0 28 Jun 2021
Explanatory Pluralism in Explainable AI Yiheng Yao XAI 33 4 0 26 Jun 2021
Using Issues to Explain Legal Decisions Trevor J. M. Bench-Capon AILaw ELM 19 10 0 25 Jun 2021
False perfection in machine prediction: Detecting and assessing circularity problems in machine learning Michael Hagmann Stefan Riezler 18 1 0 23 Jun 2021
Not all users are the same: Providing personalized explanations for sequential decision making problems Utkarsh Soni S. Sreedharan Subbarao Kambhampati 20 7 0 23 Jun 2021
Rational Shapley Values David S. Watson 25 20 0 18 Jun 2021
It's FLAN time! Summing feature-wise latent representations for interpretability An-phi Nguyen María Rodríguez Martínez FAtt 18 0 0 18 Jun 2021
Interpretable Machine Learning Classifiers for Brain Tumour Survival Prediction C. Charlton M. Poon P. Brennan Jacques D. Fleuriot 19 0 0 17 Jun 2021
Predictive Modeling of Hospital Readmission: Challenges and Solutions Shuwen Wang Xingquan Zhu OOD 34 25 0 16 Jun 2021
Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach Johannes Rabold M. Siebers Ute Schmid 31 14 0 15 Jun 2021
Counterfactual Explanations as Interventions in Latent Space Riccardo Crupi Alessandro Castelnovo D. Regoli Beatriz San Miguel González CML 16 24 0 14 Jun 2021
Prompting Contrastive Explanations for Commonsense Reasoning Tasks Bhargavi Paranjape Julian Michael Marjan Ghazvininejad Luke Zettlemoyer Hannaneh Hajishirzi ReLM LRM 32 67 0 12 Jun 2021
Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning Youri Coppens Denis Steckelmacher Catholijn M. Jonker A. Nowé 11 4 0 10 Jun 2021
On the overlooked issue of defining explanation objectives for local-surrogate explainers Rafael Poyiadzi X. Renard Thibault Laugel Raúl Santos-Rodríguez Marcin Detyniecki 21 6 0 10 Jun 2021
Explainable AI, but explainable to whom? Julie Gerlings Millie Søndergaard Jensen Arisa Shollo 43 43 0 10 Jun 2021
Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems Andrea Apicella Salvatore Giugliano Francesco Isgrò R. Prevete 14 18 0 09 Jun 2021
Amortized Generation of Sequential Algorithmic Recourses for Black-box Models Sahil Verma Keegan E. Hines John P. Dickerson 22 23 0 07 Jun 2021
Interactive Label Cleaning with Example-based Explanations Stefano Teso A. Bontempelli Fausto Giunchiglia Andrea Passerini 38 45 0 07 Jun 2021
Dissecting Generation Modes for Abstractive Summarization Models via Ablation and Attribution Jiacheng Xu Greg Durrett 38 16 0 03 Jun 2021
Towards an Explanation Space to Align Humans and Explainable-AI Teamwork G. Cabour A. Morales É. Ledoux S. Bassetto 30 5 0 02 Jun 2021
On Efficiently Explaining Graph-Based Classifiers Xuanxiang Huang Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 49 37 0 02 Jun 2021
Is Sparse Attention more Interpretable? Clara Meister Stefan Lazov Isabelle Augenstein Ryan Cotterell MILM 28 45 0 02 Jun 2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations Peter Hase Harry Xie Joey Tianyi Zhou OODD LRM FAtt 34 91 0 01 Jun 2021
Efficient Explanations With Relevant Sets Yacine Izza Alexey Ignatiev Nina Narodytska Martin C. Cooper Sasha Rubin FAtt 25 15 0 01 Jun 2021
Explanations for Monotonic Classifiers Sasha Rubin Thomas Gerspacher M. Cooper Alexey Ignatiev Nina Narodytska FAtt 16 43 0 01 Jun 2021
A unified logical framework for explanations in classifier systems Xinghan Liu E. Lorini 27 12 0 30 May 2021
Do not explain without context: addressing the blind spot of model explanations Katarzyna Wo'znica Katarzyna Pkekala Hubert Baniecki Wojciech Kretowicz El.zbieta Sienkiewicz P. Biecek 28 1 0 28 May 2021
Fooling Partial Dependence via Data Poisoning Hubert Baniecki Wojciech Kretowicz P. Biecek AAML 34 23 0 26 May 2021
Effects of interactivity and presentation on review-based explanations for recommendations Diana C. Hernandez-Bocanegra J. Ziegler 14 13 0 25 May 2021
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization Emilio Gamba B. Bogaerts Tias Guns LRM 39 6 0 25 May 2021
Argumentative XAI: A Survey Kristijonas vCyras Antonio Rago Emanuele Albini P. Baroni Francesca Toni 39 142 0 24 May 2021
On Explaining Random Forests with SAT Yacine Izza Sasha Rubin FAtt 30 72 0 21 May 2021
Explainable Machine Learning with Prior Knowledge: An Overview Katharina Beckh Sebastian Müller Matthias Jakobs Vanessa Toborek Hanxiao Tan Raphael Fischer Pascal Welke Sebastian Houben Laura von Rueden XAI 27 28 0 21 May 2021
Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty propagation Xiao Sun B. Bahmani Nikolaos N. Vlassis WaiChing Sun Yanxun Xu CML AI4CE 70 26 0 20 May 2021
Explainable Activity Recognition for Smart Home Systems Devleena Das Yasutaka Nishimura R. Vivek Naoto Takeda Sean T. Fish Thomas Ploetz Sonia Chernova 26 41 0 20 May 2021
AI and Ethics -- Operationalising Responsible AI Liming Zhu Xiwei Xu Qinghua Lu Guido Governatori Jon Whittle 36 37 0 19 May 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 34 140 0 17 May 2021
Designer-User Communication for XAI: An epistemological approach to discuss XAI design J. Ferreira Mateus de Souza Monteiro 20 4 0 17 May 2021
Abstraction, Validation, and Generalization for Explainable Artificial Intelligence Scott Cheng-Hsin Yang Tomas Folke Patrick Shafto 21 5 0 16 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 34 184 0 15 May 2021
Cause and Effect: Hierarchical Concept-based Explanation of Neural Networks Mohammad Nokhbeh Zaeem Majid Komeili CML 23 9 0 14 May 2021
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction Shauli Ravfogel Grusha Prasad Tal Linzen Yoav Goldberg 36 57 0 14 May 2021
SAT-Based Rigorous Explanations for Decision Lists Alexey Ignatiev Sasha Rubin XAI 32 44 0 14 May 2021
Discovering the Rationale of Decisions: Experiments on Aligning Learning and Reasoning Cor Steging S. Renooij Bart Verheij 7 21 0 14 May 2021
XAI Handbook: Towards a Unified Framework for Explainable AI Sebastián M. Palacio Adriano Lucieri Mohsin Munir Jörn Hees Sheraz Ahmed Andreas Dengel 25 32 0 14 May 2021
Sufficient reasons for classifier decisions in the presence of constraints Niku Gorji S. Rubin 17 3 0 12 May 2021
Intelligent interactive technologies for mental health and well-being M. Jovanovic Aleksandar Jevremovic M. Pejović-Milovančević 22 2 0 11 May 2021
Explainable Autonomous Robots: A Survey and Perspective Tatsuya Sakai Takayuki Nagai 25 68 0 06 May 2021
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification G. Chrysostomou Nikolaos Aletras 32 37 0 06 May 2021