When Does a Diffusion Model Decide What to Draw ?

arXiv:2610.05645 · cs.LG · Submitted 2026-10-05 · Read on arXiv

cs.LG

Submitted: 2026-10-05

Updated: 2026-10-05

Code: https://github.com/nssprogrammer/diffusion-commit

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 1× in this paper · explained in 9 episodes

Sources

• Theory of Speciation Transitions in Diffusion Models with General Class Structure
• A Theory of Speciation in Generative Diffusion Models on Compact Riemannian Manifolds
• The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
• Gaussian Harmony: Attaining Fairness in Diffusion-based Face Generation Models
• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks