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Explainable Artificial Intelligence (XAI): Concepts, Taxonomies,
  Opportunities and Challenges toward Responsible AI
v1v2 (latest)

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

Information Fusion (Inf. Fusion), 2019
22 October 2019
Alejandro Barredo Arrieta
Natalia Díaz Rodríguez
Javier Del Ser
Adrien Bennetot
Siham Tabik
A. Barbado
S. García
S. Gil-Lopez
Daniel Molina
Richard Benjamins
Raja Chatila
Francisco Herrera
    XAI
ArXiv (abs)PDFHTML

Papers citing "Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI"

50 / 1,485 papers shown
Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals
Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals
Marouane Il Idrissi
Agathe Fernandes Machado
Ewen Gallic
Arthur Charpentier
567
2
0
19 May 2025
Model Discovery with Grammatical Evolution. An Experiment with Prime Numbers
Model Discovery with Grammatical Evolution. An Experiment with Prime Numbers
Jakub Skrzyński
Dominik Sepioło
Antoni Ligęza
77
0
0
18 May 2025
Growable and Interpretable Neural Control with Online Continual Learning for Autonomous Lifelong Locomotion Learning Machines
Growable and Interpretable Neural Control with Online Continual Learning for Autonomous Lifelong Locomotion Learning MachinesThe international journal of robotics research (IJRR), 2025
Arthicha Srisuchinnawong
Poramate Manoonpong
CLLLRM
296
3
0
17 May 2025
X-Edit: Detecting and Localizing Edits in Images Altered by Text-Guided Diffusion Models
X-Edit: Detecting and Localizing Edits in Images Altered by Text-Guided Diffusion Models
Valentina Bazyleva
Nicolo Bonettini
Gaurav Bharaj
DiffM
263
2
0
16 May 2025
Financial Fraud Detection Using Explainable AI and Stacking Ensemble Methods
Financial Fraud Detection Using Explainable AI and Stacking Ensemble Methods
Fahad Almalki
Mehedi Masud
434
8
0
15 May 2025
Beyond the Black Box: Interpretability of LLMs in Finance
Beyond the Black Box: Interpretability of LLMs in Finance
Hariom Tatsat
Ariye Shater
AIFin
186
10
0
14 May 2025
Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
Discovering Concept Directions from Diffusion-based Counterfactuals via Latent ClusteringPattern Recognition Letters (Pattern Recogn. Lett.), 2025
Payal Varshney
Adriano Lucieri
Christoph Balada
Andreas Dengel
Sheraz Ahmed
DiffM
332
0
0
11 May 2025
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual UsersEuropean Conference on Information Systems (ECIS), 2025
Julian Rosenberger
Philipp Schröppel
Sven Kruschel
Mathias Kraus
Patrick Zschech
Maximilian Förster
FAtt
322
0
0
11 May 2025
Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena
Wasserstein Distances Made Explainable: Insights into Dataset Shifts and Transport Phenomena
Philip Naumann
Jacob R. Kauffmann
G. Montavon
262
0
0
09 May 2025
See What I Mean? CUE: A Cognitive Model of Understanding Explanations
See What I Mean? CUE: A Cognitive Model of Understanding Explanations
Tobias Labarta
Nhi Hoang
Katharina Weitz
Wojciech Samek
Sebastian Lapuschkin
Leander Weber
242
0
0
09 May 2025
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Sonal Allana
Mohan Kankanhalli
Rozita Dara
370
3
0
05 May 2025
PointExplainer: Towards Transparent Parkinson's Disease Diagnosis
PointExplainer: Towards Transparent Parkinson's Disease Diagnosis
Xuechao Wang
S. Nõmm
Junqing Huang
Kadri Medijainen
A. Toomela
Michael Ruzhansky
AAMLFAtt
182
0
0
04 May 2025
Artificial Intelligence in Government: Why People Feel They Lose Control
Artificial Intelligence in Government: Why People Feel They Lose Control
Alexander Wuttke
Adrian Rauchfleisch
Andreas Jungherr
267
2
0
02 May 2025
Enhancing ML Model Interpretability: Leveraging Fine-Tuned Large Language Models for Better Understanding of AI
Enhancing ML Model Interpretability: Leveraging Fine-Tuned Large Language Models for Better Understanding of AIEuropean Conference on Information Systems (ECIS), 2025
Jonas Bokstaller
Julia Altheimer
Julian Dormehl
Alina Buss
Jasper Wiltfang
Johannes Schneider
Maximilian Röglinger
241
0
0
02 May 2025
Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration
Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration
Vasiliki Papanikou
Danae Pla Karidi
E. Pitoura
Emmanouil Panagiotou
Eirini Ntoutsi
360
1
0
01 May 2025
Thoughts without Thinking: Reconsidering the Explanatory Value of Chain-of-Thought Reasoning in LLMs through Agentic Pipelines
Thoughts without Thinking: Reconsidering the Explanatory Value of Chain-of-Thought Reasoning in LLMs through Agentic Pipelines
R. Manuvinakurike
Emanuel Moss
E. A. Watkins
Saurav Sahay
G. Raffa
L. Nachman
LRM
203
7
0
01 May 2025
RuleKit 2: Faster and simpler rule learning
RuleKit 2: Faster and simpler rule learningSoftwareX (SoftwareX), 2025
Adam Gudyś
Cezary Maszczyk
Joanna Badura
Adam Grzelak
Marek Sikora
Łukasz Wróbel
AI4TS
137
0
0
29 Apr 2025
Newton-Puiseux Analysis for Interpretability and Calibration of Complex-Valued Neural Networks
Newton-Puiseux Analysis for Interpretability and Calibration of Complex-Valued Neural NetworksNeural Networks (NN), 2025
Piotr Migus
257
0
0
27 Apr 2025
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning
Volkan Bakir
Polat Goktas
Sureyya Akyuz
274
1
0
26 Apr 2025
SSA-UNet: Advanced Precipitation Nowcasting via Channel Shuffling
SSA-UNet: Advanced Precipitation Nowcasting via Channel Shuffling
Marco Turzi
Siamak Mehrkanoon
AI4TS
297
2
0
25 Apr 2025
Testing Individual Fairness in Graph Neural Networks
Testing Individual Fairness in Graph Neural Networks
Roya Nasiri
179
1
0
25 Apr 2025
Reliable and efficient inverse analysis using physics-informed neural networks with normalized distance functions and adaptive weight tuning
Reliable and efficient inverse analysis using physics-informed neural networks with normalized distance functions and adaptive weight tuning
Shota Deguchi
Mitsuteru Asai
PINNAI4CE
506
0
0
25 Apr 2025
Crisp complexity of fuzzy classifiers
Crisp complexity of fuzzy classifiersIEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2025
Raquel Fernandez-Peralta
Javier Fumanal-Idocin
Javier Andreu-Perez
191
1
0
22 Apr 2025
Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room
Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room
Danial Hooshyar
Gustav Šír
Yeongwook Yang
Eve Kikas
Raija Hamalainen
T. Karkkainen
Dragan Gašević
Roger Azevedo
332
5
0
22 Apr 2025
Readable Twins of Unreadable Models
Readable Twins of Unreadable Models
Krzysztof Pancerz
Piotr Kulicki
Michał Kalisz
Andrzej Burda
Maciej Stanisławski
Jaromir Sarzyński
SyDa
283
0
0
17 Apr 2025
Evolutionary Reinforcement Learning for Interpretable Decision-Making in Supply Chain Management
Evolutionary Reinforcement Learning for Interpretable Decision-Making in Supply Chain Management
Stefano Genetti
Alberto Longobardi
Giovanni Iacca
194
3
0
16 Apr 2025
"Even explanations will not help in trusting [this] fundamentally biased system": A Predictive Policing Case-Study
"Even explanations will not help in trusting [this] fundamentally biased system": A Predictive Policing Case-StudyUser Modeling, Adaptation, and Personalization (UMAP), 2025
Siddharth Mehrotra
Ujwal Gadiraju
Eva Bittner
Folkert van Delden
Catholijn M. Jonker
Myrthe L. Tielman
275
0
0
15 Apr 2025
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations
Indu Panigrahi
Sunnie S. Y. Kim
Amna Liaqat
Rohan Jinturkar
Olga Russakovsky
Ruth C. Fong
Parastoo Abtahi
FAttHAI
460
2
0
14 Apr 2025
Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-being
Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-beingInternational Conference on Evaluation of Novel Approaches to Software Engineering (ENASE), 2025
Esperança Amengual-Alcover
Antoni Jaume-i-Capó
Miquel Miró-Nicolau
Gabriel Moyà Alcover
Antonia Paniza-Fullana
273
1
0
11 Apr 2025
Uncovering the Structure of Explanation Quality with Spectral Analysis
Uncovering the Structure of Explanation Quality with Spectral Analysis
Johannes Maeß
G. Montavon
Shinichi Nakajima
Klaus-Robert Müller
Thomas Schnake
FAtt
329
0
0
11 Apr 2025
A Trustworthy By Design Classification Model for Building Energy Retrofit Decision Support
A Trustworthy By Design Classification Model for Building Energy Retrofit Decision Support
Panagiota Rempi
Sotiris Pelekis
Alexandros-Menelaos Tzortzis
Evangelos Karakolis
Christos Ntanos
D. Askounis
Dimitris Askounis
342
1
0
08 Apr 2025
AEGIS: Human Attention-based Explainable Guidance for Intelligent Vehicle Systems
AEGIS: Human Attention-based Explainable Guidance for Intelligent Vehicle SystemsInternational Conference on Human Factors in Computing Systems (CHI), 2025
Zhuoli Zhuang
Cheng-You Lu
Yu-Cheng Chang
Yu-Kai Wang
T. Do
Chin-Teng Lin
334
1
0
08 Apr 2025
The challenge of uncertainty quantification of large language models in medicine
The challenge of uncertainty quantification of large language models in medicine
Zahra Atf
Seyed Amir Ahmad Safavi-Naini
Peter Lewis
Aref Mahjoubfar
Nariman Naderi
Thomas Savage
Ali Soroush
224
18
0
07 Apr 2025
An overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainability
An overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainabilityFrontiers in Artificial Intelligence (Front. Artif. Intell.), 2025
David Herrera-Poyatos
Carlos Peláez-González
Cristina Zuheros
Andrés Herrera-Poyatos
Virilo Tejedor
F. Herrera
Rosana Montes
269
18
0
06 Apr 2025
Do We Need Responsible XR? Drawing on Responsible AI to Inform Ethical Research and Practice into XRAI / the Metaverse
Do We Need Responsible XR? Drawing on Responsible AI to Inform Ethical Research and Practice into XRAI / the Metaverse
Mark Mcgill
Joseph O'Hagan
Thomas Goodge
Graham Wilson
M. Khamis
Veronika Krauß
Jan Gugenheimer
181
0
0
06 Apr 2025
Engineering Artificial Intelligence: Framework, Challenges, and Future Direction
Engineering Artificial Intelligence: Framework, Challenges, and Future Direction
Jay Lee
Hanqi Su
Dai-Yan Ji
Takanobu Minami
AI4CE
472
4
0
03 Apr 2025
Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness
Am I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness
Juliett Suárez Ferreira
Marija Slavkovik
Jorge Casillas
FaML
370
0
0
03 Apr 2025
Graph Classification and Radiomics Signature for Identification of Tuberculous Meningitis
Graph Classification and Radiomics Signature for Identification of Tuberculous Meningitis
Snigdha Agarwal
Ganaraja V H
N. Sinha
Abhilasha Indoria
Netravathi M
Jitender Saini
162
0
0
01 Apr 2025
Towards Responsible and Trustworthy Educational Data Mining: Comparing Symbolic, Sub-Symbolic, and Neural-Symbolic AI Methods
Towards Responsible and Trustworthy Educational Data Mining: Comparing Symbolic, Sub-Symbolic, and Neural-Symbolic AI Methods
Danial Hooshyar
Eve Kikas
Yeongwook Yang
Gustav Šír
Raija Hamalainen
T. Karkkainen
Roger Azevedo
385
2
0
01 Apr 2025
LLMs for Explainable AI: A Comprehensive Survey
LLMs for Explainable AI: A Comprehensive Survey
Ahsan Bilal
David Ebert
Beiyu Lin
617
36
0
31 Mar 2025
Which LIME should I trust? Concepts, Challenges, and Solutions
Which LIME should I trust? Concepts, Challenges, and Solutions
Katharina Prasse
Sascha Marton
Udo Schlegel
Christian Bartelt
FAtt
428
8
0
31 Mar 2025
Interpretable Machine Learning in Physics: A Review
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
395
14
0
30 Mar 2025
Interpretable Cross-Sphere Multiscale Deep Learning Predicts ENSO Skilfully Beyond 2 Years
Interpretable Cross-Sphere Multiscale Deep Learning Predicts ENSO Skilfully Beyond 2 Years
Rixu Hao
Yuxin Zhao
Shaoqing Zhang
Guihua Wang
Xiong Deng
AI4ClAI4CE
288
1
0
27 Mar 2025
Explainable ICD Coding via Entity Linking
Explainable ICD Coding via Entity Linking
Leonor Barreiros
I. Coutinho
Gonçalo M. Correia
Chrysoula Zerva
315
3
0
26 Mar 2025
Uncertainty-Aware Decomposed Hybrid Networks
Uncertainty-Aware Decomposed Hybrid Networks
Sina Ditzel
Achref Jaziri
Iuliia Pliushch
Visvanathan Ramesh
UQCV
274
1
0
24 Mar 2025
Coupling deep and handcrafted features to assess smile genuineness
Coupling deep and handcrafted features to assess smile genuineness
Benedykt Pawlus
Bogdan Smolka
Jolanta Kawulok
Michal Kawulok
CVBM
292
0
0
20 Mar 2025
Logic Explanation of AI Classifiers by Categorical Explaining Functors
Logic Explanation of AI Classifiers by Categorical Explaining Functors
S. Fioravanti
Francesco Giannini
Paolo Frazzetto
Fabio Zanasi
Pietro Barbiero
202
0
0
20 Mar 2025
Explainable AI Components for Narrative Map Extraction
Explainable AI Components for Narrative Map Extraction
Brian Keith
Fausto German
Eric Krokos
Sarah Joseph
Chris North
110
3
0
19 Mar 2025
A Revisit to the Decoder for Camouflaged Object Detection
A Revisit to the Decoder for Camouflaged Object DetectionBritish Machine Vision Conference (BMVC), 2025
Seung Woo Ko
Joopyo Hong
Suyoung Kim
Seungjai Bang
Sungzoon Cho
Nojun Kwak
Hyung-Sin Kim
Joonseok Lee
207
2
0
18 Mar 2025
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need?
Xu Wu
L. Moloko
P. Bokov
Gregory K. Delipei
Joshua Kaizer
K. Ivanov
AI4CE
186
3
0
16 Mar 2025
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