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cs.CV2026
CentriQ: Calibration-Free Quantization of Diffusion Transformers via Exact Mean Centering
Nataša Jovanović, Mathieu Salzmann, Saqib Javed
Diffusion transformers (DiTs) achieve state-of-the-art image generation, but their sampling cost limits deployment. Quantizing both weights and activations to 4 bits reduces this c…
cs.CV2026
Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling
Sooyoung Ryu, Mathieu Salzmann, Saqib Javed
Post-training quantization (PTQ) is a practical path to deploy large diffusion models, but quantization noise can accumulate over the denoising trajectory and degrade generation qu…