A Latent Distribution Perspective on Evaluating and Improving Latent Generative Models

arXiv:2609.24088 · cs.CV · Submitted 2026-09-21 · Read on arXiv

cs.CV

Submitted: 2026-09-21

Updated: 2026-10-06

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

Terminology

Adaptation — 63× in this paper · explained in 1 episode
Generative Model — 45× in this paper · explained in 2 episodes
Generative Models — 18× in this paper · explained in 2 episodes
Transformer — 15× in this paper · explained in 2 episodes
Latent Space — 12× in this paper · explained in 7 episodes
Alignment — 9× in this paper · explained in 1 episode
Consistency — 8× in this paper · explained in 3 episodes
Diffusion Model — 8× in this paper · explained in 8 episodes
Diffusion Models — 7× in this paper · explained in 6 episodes
Distribution Shift — 7× in this paper · explained in 5 episodes
Fidelity — 7× in this paper · explained in 2 episodes
Distillation — 6× in this paper · explained in 2 episodes
Robustness — 6× in this paper · explained in 5 episodes
Regularization — 5× in this paper · explained in 3 episodes
Decode — 4× in this paper · explained in 2 episodes
Flow Matching — 4× in this paper · explained in 8 episodes
Latent Diffusion Model — 3× in this paper · explained in 2 episodes
Latent Diffusion Models — 3× in this paper · explained in 2 episodes
AUC — 2× in this paper · explained in 2 episodes
Adversarial Training — 2× in this paper · explained in 1 episode
Distribution Matching — 2× in this paper · explained in 2 episodes
GRPO — 2× in this paper · explained in 6 episodes
Generative Modeling — 2× in this paper · explained in 3 episodes
Latent Representation — 2× in this paper · explained in 2 episodes
Normalizing Flow — 2× in this paper · explained in 3 episodes
Normalizing Flows — 2× in this paper · explained in 4 episodes
Quantization — 2× in this paper · explained in 12 episodes
Rectified Flow — 2× in this paper · explained in 3 episodes
Reinforcement Learning — 2× in this paper · explained in 4 episodes
Wasserstein Distance — 2× in this paper · explained in 4 episodes
2-Wasserstein Distance — 1× in this paper · explained in 1 episode
AdamW Optimizer — 1× in this paper · explained in 1 episode
Contrastive Learning — 1× in this paper · explained in 5 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Flow Matching Model — 1× in this paper · explained in 2 episodes
Generalization — 1× in this paper · explained in 13 episodes
Latent Representations — 1× in this paper · explained in 3 episodes
Nash Equilibrium — 1× in this paper · explained in 2 episodes
Perceptual Alignment — 1× in this paper · explained in 2 episodes
Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Terminology

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