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cs.CV2025
SegQuant: A Semantics-Aware and Generalizable Quantization Framework for Diffusion Models
Jiaji Zhang, Ruichao Sun, Hailiang Zhao +7
Diffusion models have demonstrated exceptional generative capabilities but are computationally intensive, posing significant challenges for deployment in resource-constrained or la…
cs.CV2025
Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the-Art Image Tokenization
Kyle Sargent, Kyle Hsu, Justin Johnson +2
Since the advent of popular visual generation frameworks like VQGAN and latent diffusion models, state-of-the-art image generation systems have generally been two-stage systems tha…