Quantization-Aware Kalman Estimation for Diffusion Sampling

arXiv:2609.21407 · cs.CV · Submitted 2026-09-18 · Read on arXiv

cs.CV

Submitted: 2026-09-18

Updated: 2026-09-18

Code: https://github.com/black-forest-labs/flux

Terminology

• Quantization — 35× in this paper · explained in 12 episodes
• Diffusion Model — 30× in this paper · explained in 8 episodes
• Diffusion Models — 29× in this paper · explained in 6 episodes
• Calibration — 12× in this paper · explained in 7 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Input Bias Correction — 1× in this paper
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Noise Estimation Reconstruction — 1× in this paper
• Score Function — 1× in this paper · explained in 4 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Demystifying MMD GANs
• Playground v2.5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation
• SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
• AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
• Pseudo Numerical Methods for Diffusion Models on Manifolds
• Error Propagation Mechanisms and Compensation Strategies for Quantized Diffusion
• Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling
• Score-Based Generative Modeling through Stochastic Differential Equations
• SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers
• Fast Sampling of Diffusion Models with Exponential Integrator
• Test-Time Iterative Error Correction for Efficient Diffusion Models

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