Explainable Artificial Intelligence
This open access five-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2025, held in Istanbul, Turkey, during July 2025. The 96 revised full papers presented in these proceedings were carefully reviewed and selected from 224 s...
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| Formato: | Online |
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| Idioma: | inglés |
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Springer Nature
2025
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| Acceso en liña: | ONIX_20251128T131701_9783032083302_23 |
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| collection | Directory of Open Access Books |
| description | This open access five-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2025, held in Istanbul, Turkey, during July 2025. The 96 revised full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers are organized in the following topical sections: Volume I: Concept-based Explainable AI; human-centered Explainability; explainability, privacy, and fairness in trustworthy AI; and XAI in healthcare. Volume II: Rule-based XAI systems & actionable explainable AI; features importance-based XAI; novel post-hoc & ante-hoc XAI approaches; and XAI for scientific discovery. Volume III: Generative AI meets explainable AI; Intrinsically interpretable explainable AI; benchmarking and XAI evaluation measures; and XAI for representational alignment. Volume IV: XAI in computer vision; counterfactuals in XAI; explainable sequential decision making; and explainable AI in finance & legal frameworks for XAI technologies. Volume V: Applications of XAI; human-centered XAI & argumentation; explainable and interactive hybrid decision making; and uncertainty in explainable AI. |
| format | Online |
| id | doab-20.500.12854ir-169596 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1695962025-11-29T06:08:58Z Explainable Artificial Intelligence Guidotti, Riccardo Schmid, Ute Longo, Luca Open Access eXplainable Artificial Intelligence Artificial Intelligence Machine learning Interpretable machine learning Causal inference & explanations Ante-hoc approaches for interpretability Argumentative-based approaches for explanations Auto-encoders & explainability of latent spaces Black-boxes vs white-boxes Case-based explanations for AI systems Decomposition of neural network-based models for XAI Graph neural networks for explainability Interpreting & explaining Convolutional Neural Networks Interpretable representational learning Model-specific vs model-agnostic methods for XAI Neuro-symbolic reasoning for XAI Natural language processing for explanations Pruning methods with XAI Post-hoc methods for explainability thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation thema EDItEUR::U Computing and Information Technology::UX Applied computing thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware This open access five-volume set constitutes the refereed proceedings of the Second World Conference on Explainable Artificial Intelligence, xAI 2025, held in Istanbul, Turkey, during July 2025. The 96 revised full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers are organized in the following topical sections: Volume I: Concept-based Explainable AI; human-centered Explainability; explainability, privacy, and fairness in trustworthy AI; and XAI in healthcare. Volume II: Rule-based XAI systems & actionable explainable AI; features importance-based XAI; novel post-hoc & ante-hoc XAI approaches; and XAI for scientific discovery. Volume III: Generative AI meets explainable AI; Intrinsically interpretable explainable AI; benchmarking and XAI evaluation measures; and XAI for representational alignment. Volume IV: XAI in computer vision; counterfactuals in XAI; explainable sequential decision making; and explainable AI in finance & legal frameworks for XAI technologies. Volume V: Applications of XAI; human-centered XAI & argumentation; explainable and interactive hybrid decision making; and uncertainty in explainable AI. 2025-11-29T06:08:57Z 2025-11-29T06:08:57Z 2025-11-28T12:20:14Z 2026 book ONIX_20251128T131701_9783032083302_23 https://library.oapen.org/handle/20.500.12657/108665 9783032083302 9783032083296 https://directory.doabooks.org/handle/20.500.12854/169596 eng Communications in Computer and Information Science; Artificial Intelligence (R0) open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/108665/1/9783032083302.pdf Springer Nature Springer 10.1007/978-3-032-08330-2 10.1007/978-3-032-08330-2 9fa3421d-f917-4153-b9ab-fc337c396b5a 0dc5aca1-8375-4746-b6a1-a1ac6b0fc2ec 9783032083302 9783032083296 Springer 420 Cham [...] open access |
| spellingShingle | Open Access eXplainable Artificial Intelligence Artificial Intelligence Machine learning Interpretable machine learning Causal inference & explanations Ante-hoc approaches for interpretability Argumentative-based approaches for explanations Auto-encoders & explainability of latent spaces Black-boxes vs white-boxes Case-based explanations for AI systems Decomposition of neural network-based models for XAI Graph neural networks for explainability Interpreting & explaining Convolutional Neural Networks Interpretable representational learning Model-specific vs model-agnostic methods for XAI Neuro-symbolic reasoning for XAI Natural language processing for explanations Pruning methods with XAI Post-hoc methods for explainability thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation thema EDItEUR::U Computing and Information Technology::UX Applied computing thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware Explainable Artificial Intelligence |
| title | Explainable Artificial Intelligence |
| title_full | Explainable Artificial Intelligence |
| title_fullStr | Explainable Artificial Intelligence |
| title_full_unstemmed | Explainable Artificial Intelligence |
| title_short | Explainable Artificial Intelligence |
| title_sort | explainable artificial intelligence |
| topic | Open Access eXplainable Artificial Intelligence Artificial Intelligence Machine learning Interpretable machine learning Causal inference & explanations Ante-hoc approaches for interpretability Argumentative-based approaches for explanations Auto-encoders & explainability of latent spaces Black-boxes vs white-boxes Case-based explanations for AI systems Decomposition of neural network-based models for XAI Graph neural networks for explainability Interpreting & explaining Convolutional Neural Networks Interpretable representational learning Model-specific vs model-agnostic methods for XAI Neuro-symbolic reasoning for XAI Natural language processing for explanations Pruning methods with XAI Post-hoc methods for explainability thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation thema EDItEUR::U Computing and Information Technology::UX Applied computing thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware |
| topic_facet | Open Access eXplainable Artificial Intelligence Artificial Intelligence Machine learning Interpretable machine learning Causal inference & explanations Ante-hoc approaches for interpretability Argumentative-based approaches for explanations Auto-encoders & explainability of latent spaces Black-boxes vs white-boxes Case-based explanations for AI systems Decomposition of neural network-based models for XAI Graph neural networks for explainability Interpreting & explaining Convolutional Neural Networks Interpretable representational learning Model-specific vs model-agnostic methods for XAI Neuro-symbolic reasoning for XAI Natural language processing for explanations Pruning methods with XAI Post-hoc methods for explainability thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation thema EDItEUR::U Computing and Information Technology::UX Applied computing thema EDItEUR::U Computing and Information Technology::UK Computer hardware::UKN Network hardware |
| url | ONIX_20251128T131701_9783032083302_23 |