AI RESEARCH
BADiff: Bandwidth Adaptive Diffusion Model
arXiv CS.CV
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ArXi:2510.21366v3 Announce Type: replace In this work, we propose a novel framework to enable diffusion models to adapt their generation quality based on real-time network bandwidth constraints. Traditional diffusion models produce high-fidelity images by performing a fixed number of denoising steps, regardless of downstream transmission limitations. However, in practical cloud-to-device scenarios, limited bandwidth often necessitates heavy compression, leading to loss of fine textures and wasted computation. To address this, we