On-demand Quantization for Green Federated Generative Diffusion in Mobile Edge Networks

The author proposes an on-demand quantized energy-efficient federated diffusion approach to address challenges in training large generative diffusion models in mobile edge networks. This method significantly reduces energy consumption and model size while maintaining data quality.