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2nd World Conference on Explainable Artificial Intelligence, xAI 2024

Longo, L. [ed.]; Lapuschkin, S. [ed.]; Seifert, C. [ed.]

English Scientific

Published: Springer Science and Business Media B.V. 2024

Conference: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 2024-07-17 [Valletta, Malta]

Series: Communications in Computer and Information Science 1865-0929 1865-0937, 2153 CCIS

Identifiers

MTMT: 35200055
ISBN: 9783031637865

Chapters

Gallée L. et al. Evaluating the Explainability of Attributes and Prototypes for a Medical Classification Model. (2024) In: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 pp. 43-56
Amara Kenza et al. Challenges and Opportunities in Text Generation Explainability. (2024) In: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 pp. 244-264
Rutinowski Jerome et al. Benchmarking Trust: A Metric for Trustworthy Machine Learning. (2024) In: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 pp. 287-307
Huang Qi et al. Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI. (2024) In: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 pp. 308-331
Llorente Oscar et al. Evaluating Neighbor Explainability for Graph Neural Networks. (2024) In: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 pp. 383-402
Perotti Alan et al. Explainability, Quantified: Benchmarking XAI Techniques. (2024) In: 2nd World Conference on Explainable Artificial Intelligence, xAI 2024 pp. 421-444

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2025-04-24 12:42

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