arxiv
PublishedJuly 16, 2026 at 4:00 AM
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Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges
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arXiv:2607.13045v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a key paradigm for privacy-preserving collaborative model training across distributed and heterogeneous data sources. By keeping raw data local, FL addresses data confidentiality concerns, yet it does not resolv
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Originally published on arxiv ↗