Denoising Diffusion Generative Models Secretly Calculate Attentions

arXiv:2609.00885 · cs.AI, cs.CV, cs.LG, cs.NE · Submitted 2026-09-01 · Read on arXiv

cs.AI, cs.CV, cs.LG, cs.NE

Submitted: 2026-09-01

Updated: 2026-09-01

Terminology

• Attention Mechanism — 25× in this paper · explained in 3 episodes
• Transformer — 16× in this paper · explained in 2 episodes
• Diffusion Model — 12× in this paper · explained in 8 episodes
• Diffusion Models — 8× in this paper · explained in 6 episodes
• Latent Space — 5× in this paper · explained in 7 episodes
• Loss Function — 5× in this paper · explained in 2 episodes
• Latent Representation — 4× in this paper · explained in 2 episodes
• Diffusion Process — 3× in this paper · explained in 2 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Score Function — 3× in this paper · explained in 4 episodes
• Core — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Mean-Squared Error — 1× in this paper
• Quadratic Programming (QP) — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Variational Auto-Encoder — 1× in this paper

Sources

• Speed Always Wins: A Survey on Efficient Architectures for Large Language Models
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• A Geometric Perspective on Autoencoders
• Denoising Diffusion Implicit Models
• Understanding Diffusion Models: A Unified Perspective
• Tree Cross Attention

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