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FED-HARGPT: A Hybrid Centralized-Federated Approach of a Transformer-based Archi

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1 SIGNALFIRST DETECTED 27 March 2026
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27 Mar
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27 Mar
Agentic Trust Coordination for Federated Learning through Adaptive Thresholding and Autonomous Decision Making in Sustainable and Resilient Industrial Networks

arXiv:2603.25334v1 Announce Type: new Abstract: Distributed intelligence in industrial networks increasingly integrates sensing, communication, and computation across

REPORT · WHAT · ArXiv CS.AIOPEN STORY
4 May
FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources

arXiv:2605.00011v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative intelligence across decentralized data source devices in a privacy-preserving way.

REPORT · WHAT · ArXiv CS.AIOPEN STORY
16 Sept
Domain Generalization for Smartphone-Based Human Activity Recognition: A Systematic Analysis of Components and Interactions

arXiv:2609.14863v1 Announce Type: new Abstract: Smartphone-based Human Activity Recognition (HAR) models often degrade under distribution shifts caused by changes in users,

REPORT · WHAT · ArXiv CS.AIOPEN STORY
14 Aug
Hierarchical Federated Transfer Learning in Digital Twin-Based Vehicular Networks

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

REPORT · WHEN · ArXiv CS.AIOPEN STORY
30 Apr
Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization

arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process

REPORT · WHAT · ArXiv CS.AIOPEN STORY
20 May
KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition

arXiv:2605.19031v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional

REPORT · WHAT · ArXiv CS.AIOPEN STORY
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