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Explanation in Artificial Intelligence: Insights from the Social
  Sciences
v1v2v3 (latest)

Explanation in Artificial Intelligence: Insights from the Social Sciences

22 June 2017
Tim Miller
    XAI
ArXiv (abs)PDFHTML

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

50 / 1,336 papers shown
Title
Deep Explainable Learning with Graph Based Data Assessing and Rule
  Reasoning
Deep Explainable Learning with Graph Based Data Assessing and Rule Reasoning
Yuanlong Li
Gaopan Huang
Min Zhou
Chuan Fu
Honglin Qiao
Yan He
186
1
0
09 Nov 2022
Privacy Meets Explainability: A Comprehensive Impact Benchmark
Privacy Meets Explainability: A Comprehensive Impact Benchmark
S. Saifullah
Dominique Mercier
Adriano Lucieri
Andreas Dengel
Sheraz Ahmed
161
20
0
08 Nov 2022
Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoT
Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoTHawaii International Conference on System Sciences (HICSS), 2022
Jiaheng Xie
Xiaohang Zhao
Xiang Liu
Xiao Fang
OOD
323
3
0
08 Nov 2022
ViT-CX: Causal Explanation of Vision Transformers
ViT-CX: Causal Explanation of Vision TransformersInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Weiyan Xie
Xiao-hui Li
Caleb Chen Cao
Nevin L.Zhang
ViT
290
31
0
06 Nov 2022
A $k$-additive Choquet integral-based approach to approximate the SHAP
  values for local interpretability in machine learning
A kkk-additive Choquet integral-based approach to approximate the SHAP values for local interpretability in machine learningArtificial Intelligence (AIJ), 2022
G. D. Pelegrina
L. Duarte
M. Grabisch
FAttTDI
221
48
0
03 Nov 2022
A General Search-based Framework for Generating Textual Counterfactual
  Explanations
A General Search-based Framework for Generating Textual Counterfactual ExplanationsAAAI Conference on Artificial Intelligence (AAAI), 2022
Daniel Gilo
Shaul Markovitch
LRM
247
3
0
01 Nov 2022
Towards Human Cognition Level-based Experiment Design for Counterfactual
  Explanations (XAI)
Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations (XAI)
M. Nizami
Muhammad Yaseen Khan
Alessandro Bogliolo
196
3
0
31 Oct 2022
Artificial intelligence in government: Concepts, standards, and a
  unified framework
Artificial intelligence in government: Concepts, standards, and a unified frameworkJournal of Grid Computing (J. Grid Comput.), 2022
Vince J. Straub
Deborah Morgan
Jonathan Bright
Helen Z. Margetts
AI4TS
199
56
0
31 Oct 2022
Feature Necessity & Relevancy in ML Classifier Explanations
Feature Necessity & Relevancy in ML Classifier ExplanationsInternational Conference on Tools and Algorithms for Construction and Analysis of Systems (TACAS), 2022
Xuanxiang Huang
Martin C. Cooper
António Morgado
Jordi Planes
Sasha Rubin
FAtt
209
22
0
27 Oct 2022
Painting the black box white: experimental findings from applying XAI to
  an ECG reading setting
Painting the black box white: experimental findings from applying XAI to an ECG reading settingMachine Learning and Knowledge Extraction (MLKE), 2022
F. Cabitza
M. Cameli
Andrea Campagner
Chiara Natali
Luca Ronzio
172
16
0
27 Oct 2022
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using
  Deep Transformers and Explainable Artificial Intelligence
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence
M. Jafari
A. Shoeibi
Navid Ghassemi
Jónathan Heras
Saiguang Ling
...
Shuihua Wang
R. Alizadehsani
Juan M Gorriz
U. Acharya
Hamid Alinejad-Rokny
MedIm
253
12
0
26 Oct 2022
Does Self-Rationalization Improve Robustness to Spurious Correlations?
Does Self-Rationalization Improve Robustness to Spurious Correlations?Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Alexis Ross
Matthew E. Peters
Ana Marasović
LRM
241
15
0
24 Oct 2022
Causal Explanation for Reinforcement Learning: Quantifying State and
  Temporal Importance
Causal Explanation for Reinforcement Learning: Quantifying State and Temporal Importance
Xiaoxiao Wang
Fanyu Meng
Xin Liu
Z. Kong
Xin Chen
XAICMLFAtt
317
4
0
24 Oct 2022
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR)
  for Metaverses
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for MetaversesACM Computing Surveys (ACM CSUR), 2022
Adnan Qayyum
M. A. Butt
Hassan Ali
Muhammad Usman
O. Halabi
Ala I. Al-Fuqaha
Q. Abbasi
Muhammad Ali Imran
Junaid Qadir
219
58
0
24 Oct 2022
Logic-Based Explainability in Machine Learning
Logic-Based Explainability in Machine Learning
Sasha Rubin
LRMXAI
468
58
0
24 Oct 2022
A Survey on Graph Counterfactual Explanations: Definitions, Methods,
  Evaluation, and Research Challenges
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research ChallengesACM Computing Surveys (ACM CSUR), 2022
Mario Alfonso Prado-Romero
Bardh Prenkaj
Giovanni Stilo
F. Giannotti
CML
261
42
0
21 Oct 2022
Redefining Counterfactual Explanations for Reinforcement Learning:
  Overview, Challenges and Opportunities
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and OpportunitiesACM Computing Surveys (ACM CSUR), 2022
Jasmina Gajcin
Ivana Dusparic
CMLOffRL
350
21
0
21 Oct 2022
Diffusion Visual Counterfactual Explanations
Diffusion Visual Counterfactual ExplanationsNeural Information Processing Systems (NeurIPS), 2022
Maximilian Augustin
Valentyn Boreiko
Francesco Croce
Matthias Hein
DiffMBDL
205
95
0
21 Oct 2022
Towards Human-centered Explainable AI: A Survey of User Studies for
  Model Explanations
Towards Human-centered Explainable AI: A Survey of User Studies for Model ExplanationsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Yao Rong
Tobias Leemann
Thai-trang Nguyen
Lisa Fiedler
Peizhu Qian
Vaibhav Unhelkar
Tina Seidel
Gjergji Kasneci
Enkelejda Kasneci
ELM
312
163
0
20 Oct 2022
On Trustworthy Decision-Making Process of Human Drivers from the View of
  Perceptual Uncertainty Reduction
On Trustworthy Decision-Making Process of Human Drivers from the View of Perceptual Uncertainty Reduction
Huanjie Wang
Haibin Liu
Wenshuo Wang
Lijun Sun
168
5
0
15 Oct 2022
Machine Learning in Transaction Monitoring: The Prospect of xAI
Machine Learning in Transaction Monitoring: The Prospect of xAIHawaii International Conference on System Sciences (HICSS), 2022
Julie Gerlings
Ioanna D. Constantiou
114
4
0
14 Oct 2022
Saliency Map Verbalization: Comparing Feature Importance Representations
  from Model-free and Instruction-based Methods
Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods
Nils Feldhus
Leonhard Hennig
Maximilian Dustin Nasert
Christopher Ebert
Robert Schwarzenberg
Sebastian Möller
FAtt
191
22
0
13 Oct 2022
Challenges in Explanation Quality Evaluation
Challenges in Explanation Quality Evaluation
Hendrik Schuff
Heike Adel
Peng Qi
Ngoc Thang Vu
XAI
214
3
0
13 Oct 2022
A Survey on Explainable Anomaly Detection
A Survey on Explainable Anomaly DetectionACM Transactions on Knowledge Discovery from Data (TKDD), 2022
Zhong Li
Yuxuan Zhu
M. Leeuwen
315
127
0
13 Oct 2022
On the Explainability of Natural Language Processing Deep Models
On the Explainability of Natural Language Processing Deep ModelsACM Computing Surveys (ACM CSUR), 2022
Julia El Zini
M. Awad
240
110
0
13 Oct 2022
Assessing Out-of-Domain Language Model Performance from Few Examples
Assessing Out-of-Domain Language Model Performance from Few ExamplesConference of the European Chapter of the Association for Computational Linguistics (EACL), 2022
Prasann Singhal
Jarad Forristal
Xi Ye
Greg Durrett
LRM
198
6
0
13 Oct 2022
Explaining Online Reinforcement Learning Decisions of Self-Adaptive
  Systems
Explaining Online Reinforcement Learning Decisions of Self-Adaptive SystemsInternational Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), 2022
Felix Feit
Andreas Metzger
Klaus Pohl
94
15
0
12 Oct 2022
Experiential Explanations for Reinforcement Learning
Experiential Explanations for Reinforcement Learning
Amal Alabdulkarim
Madhuri Singh
Gennie Mansi
Kaely Hall
Mark O. Riedl
Mark O. Riedl
OffRL
496
5
0
10 Oct 2022
A Detailed Study of Interpretability of Deep Neural Network based Top
  Taggers
A Detailed Study of Interpretability of Deep Neural Network based Top Taggers
Ayush Khot
Mark S. Neubauer
Avik Roy
AAML
445
22
0
09 Oct 2022
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features
  for a Disentangled, Interpretable, and Controllable Text-Guided Face
  Manipulation
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face ManipulationInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022
Chenliang Zhou
Fangcheng Zhong
Steven Chacko
CLIP
421
21
0
08 Oct 2022
Quantitative Metrics for Evaluating Explanations of Video DeepFake
  Detectors
Quantitative Metrics for Evaluating Explanations of Video DeepFake DetectorsBritish Machine Vision Conference (BMVC), 2022
Federico Baldassarre
Quentin Debard
Gonzalo Fiz Pontiveros
Tri Kurniawan Wijaya
206
5
0
07 Oct 2022
What Do End-Users Really Want? Investigation of Human-Centered XAI for
  Mobile Health Apps
What Do End-Users Really Want? Investigation of Human-Centered XAI for Mobile Health Apps
Katharina Weitz
Alexander Zellner
Elisabeth André
96
6
0
07 Oct 2022
Exploring Effectiveness of Explanations for Appropriate Trust: Lessons
  from Cognitive Psychology
Exploring Effectiveness of Explanations for Appropriate Trust: Lessons from Cognitive Psychology
R. Verhagen
Siddharth Mehrotra
Mark Antonius Neerincx
Catholijn M. Jonker
Myrthe L. Tielman
103
2
0
05 Oct 2022
On the Influence of Cognitive Styles on Users' Understanding of
  Explanations
On the Influence of Cognitive Styles on Users' Understanding of ExplanationsInternational Conference on Interaction Sciences (ICIS), 2022
Lara Riefle
Patrick Hemmer
Carina Benz
Michael Vossing
Jannik Pries
200
7
0
05 Oct 2022
Concise and interpretable multi-label rule sets
Concise and interpretable multi-label rule setsIndustrial Conference on Data Mining (IDM), 2022
Martino Ciaperoni
Han Xiao
Aristides Gionis
165
1
0
04 Oct 2022
"Help Me Help the AI": Understanding How Explainability Can Support
  Human-AI Interaction
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI InteractionInternational Conference on Human Factors in Computing Systems (CHI), 2022
Sunnie S. Y. Kim
E. A. Watkins
Olga Russakovsky
Ruth C. Fong
Andrés Monroy-Hernández
294
145
0
02 Oct 2022
Using Argumentation Schemes to Model Legal Reasoning
Using Argumentation Schemes to Model Legal Reasoning
Trevor J. M. Bench-Capon
Katie Atkinson
ELMAILaw
63
5
0
01 Oct 2022
BIASeD: Bringing Irrationality into Automated System Design
BIASeD: Bringing Irrationality into Automated System Design
Aditya Gulati
M. Lozano
Bruno Lepri
Nuria Oliver
330
8
0
01 Oct 2022
Contrastive Corpus Attribution for Explaining Representations
Contrastive Corpus Attribution for Explaining RepresentationsInternational Conference on Learning Representations (ICLR), 2022
Christy Lin
Hugh Chen
Chanwoo Kim
Su-In Lee
SSL
167
9
0
30 Sep 2022
Variance Tolerance Factors For Interpreting ALL Neural Networks
Variance Tolerance Factors For Interpreting ALL Neural NetworksIEEE International Joint Conference on Neural Network (IJCNN), 2022
Sichao Li
Amanda S. Barnard
FAtt
208
4
0
28 Sep 2022
Assessing Digital Language Support on a Global Scale
Assessing Digital Language Support on a Global ScaleInternational Conference on Computational Linguistics (COLING), 2022
Gary F. Simons
Abbey L Thomas
Chad White
ELM
130
15
0
27 Sep 2022
Greybox XAI: a Neural-Symbolic learning framework to produce
  interpretable predictions for image classification
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classificationKnowledge-Based Systems (KBS), 2022
Adrien Bennetot
Gianni Franchi
Javier Del Ser
Raja Chatila
Natalia Díaz Rodríguez
AAML
220
32
0
26 Sep 2022
Towards Faithful Model Explanation in NLP: A Survey
Towards Faithful Model Explanation in NLP: A SurveyComputational Linguistics (CL), 2022
Qing Lyu
Marianna Apidianaki
Chris Callison-Burch
XAI
490
166
0
22 Sep 2022
Counterfactual Explanations Using Optimization With Constraint Learning
Counterfactual Explanations Using Optimization With Constraint Learning
Donato Maragno
Tabea E. Rober
Ilker Birbil
CML
305
13
0
22 Sep 2022
Understandable Robots
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Shikhar Kumar
119
14
0
22 Sep 2022
Computing Abductive Explanations for Boosted Trees
Computing Abductive Explanations for Boosted TreesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Gilles Audemard
Jean-Marie Lagniez
Pierre Marquis
N. Szczepanski
137
20
0
16 Sep 2022
Model interpretation using improved local regression with variable
  importance
Model interpretation using improved local regression with variable importance
Gilson Y. Shimizu
Rafael Izbicki
A. Carvalho
FAtt
178
3
0
12 Sep 2022
A Causal-based Approach to Explain, Predict and Prevent Failures in
  Robotic Tasks
A Causal-based Approach to Explain, Predict and Prevent Failures in Robotic Tasks
Maximilian Diehl
Karinne Ramirez-Amaro
CML
225
29
0
12 Sep 2022
Explaining Results of Multi-Criteria Decision Making
Explaining Results of Multi-Criteria Decision MakingJournal of Multi-Criteria Decision Analysis (MCDA), 2022
Martin Erwig
Prashant Kumar
27
0
0
10 Sep 2022
Shapley value-based approaches to explain the robustness of classifiers
  in machine learning
Shapley value-based approaches to explain the robustness of classifiers in machine learning
G. D. Pelegrina
S. Siraj
FAtt
129
3
0
09 Sep 2022
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