Who Cited It

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

2019 · Information Fusion · 9,796 citations · 6 from inside this corpus

Alejandro Barredo Arrieta low, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-López, Daniel Molina, Richard Benjamins, Raja Chatila, Francisco Herrera

No abstract in the source record.

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challe… (2019)Explainable Artificial Intell…A Survey on Transfer Learning (2009)A Survey on Transfer LearningArtificial intelligence: a modern approach (1995)Artificial intelligence: a mo…"Why Should I Trust You?" (2016)"Why Should I Trust You?"Advances in Neural Information Processing Systems 19 (2007)Advances in Neural Informatio…Induction of Decision Trees (1986)Induction of Decision TreesAdvances in Neural Information Processing Systems 28 (2015)Advances in Neural Informatio…Distilling the Knowledge in a Neural Network (2015)Distilling the Knowledge in a…On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Deg… (2024)On a Method to Measure Superv…Advances in Neural Information Processing Systems 29 (2016)Advances in Neural Informatio…Induction of decision trees (1986)Induction of decision treesStop explaining black box machine learning models for high stakes decisions and use inter… (2019)Stop explaining black box mac…Explaining and Harnessing Adversarial Examples (2014)Explaining and Harnessing Adv…A Unified Approach to Interpreting Model Predictions (2017)A Unified Approach to Interpr…Attention Is All You Need (2025)Attention Is All You NeedClassification And Regression Trees (2017)Classification And Regression…Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI) (2018)Peeking Inside the Black-Box:…Intriguing properties of neural networks (2013)Intriguing properties of neur…Communication-Efficient Learning of Deep Networks from Decentralized Data (2016)Communication-Efficient Learn…A survey of methods for explaining black box models (2019)A survey of methods for expla…Towards A Rigorous Science of Interpretable Machine Learning (2017)Towards A Rigorous Science of…Advances in neural information processing systems 11 (1999)Federated Learning: Strategies for Improving Communication Efficiency (2016)Federated Learning: Strategie…2009 International Joint Conference on Artificial Intelligence (2009)2009 International Joint Conf…Methods for interpreting and understanding deep neural networks (2017)Methods for interpreting and …Axiomatic Attribution for Deep Networks (2017)Axiomatic Attribution for Dee…Conditional Random Fields as Recurrent Neural Networks (2015)Conditional Random Fields as …Learning Important Features Through Propagating Activation Differences (2017)Learning Important Features T…Definitions, methods, and applications in interpretable machine learning (2019)Definitions, methods, and app…Robust Physical-World Attacks on Deep Learning Visual Classification (2018)Robust Physical-World Attacks…Anchors: High-Precision Model-Agnostic Explanations (2018)Anchors: High-Precision Model…Explainable AI: A Review of Machine Learning Interpretability Methods (2020)Explainable AI: A Review of M…A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI (2020)A Survey on Explainable Artif…Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence (2023)Interpreting Black-Box Models…Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw… (2023)Explainable Artificial Intell…Pre-trained models for natural language processing: A survey (2020)Pre-trained models for natura…The effects of explainability and causability on perception, trust, and acceptance: Impli… (2020)
36 of 42 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
A Survey on Transfer Learning200923,670
Artificial intelligence: a modern approach199522,262
"Why Should I Trust You?"201616,210
Advances in Neural Information Processing Systems 19200715,653
Induction of Decision Trees198615,020
Advances in Neural Information Processing Systems 28201514,672
Distilling the Knowledge in a Neural Network201514,099
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Deg…202413,528
Advances in Neural Information Processing Systems 29201613,474
Induction of decision trees198612,427
Stop explaining black box machine learning models for high stakes decisions and use inter…20199,924
Explaining and Harnessing Adversarial Examples20148,146
A Unified Approach to Interpreting Model Predictions20177,625
Attention Is All You Need20257,133
Classification And Regression Trees20176,721
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)20186,166
Intriguing properties of neural networks20135,739
Communication-Efficient Learning of Deep Networks from Decentralized Data20165,190
A survey of methods for explaining black box models20194,992
Towards A Rigorous Science of Interpretable Machine Learning20173,190
Advances in neural information processing systems 1119993,187
Federated Learning: Strategies for Improving Communication Efficiency20163,050
2009 International Joint Conference on Artificial Intelligence20092,806
Methods for interpreting and understanding deep neural networks20172,763
Axiomatic Attribution for Deep Networks20172,650
Conditional Random Fields as Recurrent Neural Networks20152,437
Learning Important Features Through Propagating Activation Differences20172,379
Definitions, methods, and applications in interpretable machine learning20192,161
Robust Physical-World Attacks on Deep Learning Visual Classification20182,154
Anchors: High-Precision Model-Agnostic Explanations20182,124

What cites it, inside the corpus

PaperYearCited
Explainable AI: A Review of Machine Learning Interpretability Methods20202,907
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI20202,377
Interpreting Black-Box Models: A Review on Explainable Artificial Intelligence20231,981
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustw…20231,679
Pre-trained models for natural language processing: A survey20201,521
The effects of explainability and causability on perception, trust, and acceptance: Impli…20201,420

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Topics

Explainable Artificial Intelligence (XAI)Computer Science
Adversarial Robustness in Machine LearningComputer Science
Artificial Intelligence in Healthcare and EducationMedicine

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  • supports668 reference(s) recorded.
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