Does Uniform Discrete Diffusion Need Time?

arXiv:2609.30977 · cs.LG, cs.AI, cs.CL · Submitted 2026-09-25 · Read on arXiv

cs.LG, cs.AI, cs.CL

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Diffusion Model — 28× in this paper · explained in 8 episodes
• Diffusion Models — 27× in this paper · explained in 6 episodes
• Transformer — 15× in this paper · explained in 2 episodes
• Perplexity — 10× in this paper · explained in 3 episodes
• Hamming Distance — 5× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 4× in this paper
• Generative Modeling — 3× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• In International Conference on Learning Representations — 2× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Block Diffusion — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Gradient Flow — 1× in this paper · explained in 2 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation
• What Time Is It? How Data Geometry Makes Time Conditioning Optional for Flow Matching
• The Principles of Diffusion Models
• The Geometry of Noise: Why Diffusion Models Don't Need Noise Conditioning
• Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models
• Dream 7B: Diffusion Large Language Models

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