Author

Dirk R. Englund

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#machine learning Preprint Sep 2026

AIR-LLM: Broadcasting AI Weights over Radio for Memory-Free Edge LLM Inference via RF Computing

Next-generation large language models (LLMs) are expanding from the cloud to ubiquitous edge devices. However, edge devices typically either lack the memory to store increasingly large LLM weights or, even with enough memory, spend unaffordable energy on loading the weights. This raises our question: can an edge device...

Zhi-Hui Gao, Ting-Jun Chen, Dirk R. Englund · 0 citations

#machine learning Preprint Sep 2026

Radio-Frequency Convolutional Neural Networks

Radio-frequency convolutional neural networks (RF-CNNs), which repurpose existing communication hardware for CNN inference, are introduced and suggest that deployed wireless infrastructure can bring efficient, state-of-the-art AI inference to the billions of devices it already connects.

Zhi-Hui Gao, Shi-Fan Ma, Yi-Ran Chen et al. · 0 citations