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Explainable Artificial Intelligence : Third World Conference, xAI 2025, Istanbul, Turkey, July 9–11, 2025, Proceedings, Part V / edited by Riccardo Guidotti, Ute Schmid, Luca Longo.

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Format:
Book
Author/Creator:
Guidotti, Riccardo.
Contributor:
Schmid, U. (Ute)
Longo, Luca.
Series:
Communications in Computer and Information Science, 1865-0937 ; 2580
Language:
English
Subjects (All):
Artificial intelligence.
Natural language processing (Computer science).
Application software.
Computer networks.
Artificial Intelligence.
Natural Language Processing (NLP).
Computer and Information Systems Applications.
Computer Communication Networks.
Local Subjects:
Artificial Intelligence.
Natural Language Processing (NLP).
Computer and Information Systems Applications.
Computer Communication Networks.
Physical Description:
1 online resource (603 pages)
Edition:
1st ed. 2026.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
Summary:
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.
Contents:
Applications of XAI
Global Explanations of Expected Goal Models in Football
Comprehensive Explanations Using Natural Language Queries
A Human-in-the-Loop Approach to Learning Social Norms as Defeasible Logical Constraints
A Cautionary Tale About ''Neutrally'' Informative AI Tools Ahead of the 2025 Federal Elections in Germany
Human-Centered XAI & Argumentation
Evaluating Argumentation Graphs as Global Explainable Surrogate Models for Dense Neural Networks and their Comparison with Decision Trees
Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI
Explanations for Medical Diagnosis Predictions Based on Argumentation Schemes
Spectral Occlusion - Attribution Beyond Spatial Relevance Heatmaps
Non-experts' Trust in XAI is Unreasonably High
Explainable and Interactive Hybrid Decision Making
Exploring Annotator Disagreement in Sexism Detection: Insights from Explainable AI
Can You Regulate Your Emotions? An Empirical Investigation of the Influence of AI Explanations and Emotion Regulation on Human Decision-Making Factors
When Bias Backfires: The Modulatory Role of Counterfactual Explanations on the Adoption of Algorithmic Bias in XAI-Supported Human Decision-Making
Understanding Disagreement Between Humans and Machines in XAI: Robustness, Fidelity, and Region-Based Explanations in Automatic Neonatal Pain Assessment
On Combining Embeddings, Ontology and LLM to Retrieve Semantically Similar Quranic Verses and Generate their Explanations
Uncertainty in Explainable AI
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models
Explaining Low Perception Model Competency with High-Competency Counterfactuals
Uncertainty Propagation in XAI: A Comparison of Analytical and Empirical Estimators.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-032-08333-8
9783032083333
OCLC:
1561173943

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