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Author

Ya-Lan Jiang

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FedTuneFM: Federated Fine-Tuning of Foundation Models for Mobile Edge Computing via Adaptive Compression and Attention Alignment

Federated Learning (FL) has emerged as a promising paradigm for fine-tuning large-scale Foundation Models (FMs) in distributed environments while preserving data privacy. However, efficiently adapting FMs in FL remains challenging, especially in mobile edge computing scenarios where devices are resource-constrained and...

Ya-Lan Jiang, Bin Song · 0 citations

CSAFL: Communication-Efficient and Staleness-Aware Asynchronous Federated Learning for LEO Satellite Networks

The Satellite Internet of Things (SIoT) leverages low Earth orbit (LEO) satellite constellations to support wide-area, real-time, and intelligent services such as disaster monitoring, ship tracking, and environmental sensing. These tasks demand collaborative model training across multiple satellites to improve predicti...

Ya-Lan Jiang, Bin Song, J. Qi et al. · 0 citations

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