arXiv:2608.20518v1 Announce Type: new Abstract: In Federated Learning (FL), the communication topology is a runtime variable rather than a fixed design choice, since links and
arXiv:2603.25334v1 Announce Type: new Abstract: Distributed intelligence in industrial networks increasingly integrates sensing, communication, and computation across
arXiv:2604.00050v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising technique for training language models on distributed and private datasets of
arXiv:2603.24601v1 Announce Type: cross Abstract: The study explores a hybrid centralized-federated approach for Human Activity Recognition (HAR) using a Transformer-based
arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process
arXiv:2608.11532v1 Announce Type: cross Abstract: In recent research on the Digital Twin-based Vehicular Ad hoc Network(DT-VANET), Federated Learning (FL) has shown its ability to
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