Accelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques
Diffusion large language models (dLLMs) offer a theoretical advantage in parallel generation over standard autoregressive models. However, parallel generation alone does not guarantee practical speedups. Realizing this efficiency requires specialized inference mechanisms, such as diffusion-aware caching and reuse. Consequently, as inference efficiency becomes a prerequisite for practical deployment, recent research has actively explored acceleration techniques across algorithms, architectures, and systems. However, rigorous comparisons remain difficult, as end-to-end latency stems from intrica
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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- PossiblePossibly related (embedding) · 62%thu-pacman/chitu →
- PossiblePossibly related (embedding) · 59%DiffusionGemma: 4x faster text generation →
- PossiblePossibly related (embedding) · 57%minimal-diffusion-lm →
- PossiblePossibly related (embedding) · 54%What if context compression is a diffusion noise function? Proposal + honest results from untrained-model experiments [R] →
- PossiblePossibly related (embedding) · 52%Scaling Properties of Continuous Diffusion Spoken Language Models - Apple Machine Learning Research →
- FuzzySimilar title/name (fuzzy) · 59%stabilityai/stable-diffusion-xl-base-1.0 →
“Fuzzy title match (0.73): “Accelerating Masked Diffusion Large Language Models: A Surve” ≈ “stabilityai/stable-diffusion-xl-base-1.0””
- FuzzySimilar title/name (fuzzy) · 59%CompVis/stable-diffusion-v1-4 →
“Fuzzy title match (0.73): “Accelerating Masked Diffusion Large Language Models: A Surve” ≈ “CompVis/stable-diffusion-v1-4””
- FuzzySimilar title/name (fuzzy) · 59%stabilityai/stable-diffusion-3.5-large →
“Fuzzy title match (0.73): “Accelerating Masked Diffusion Large Language Models: A Surve” ≈ “stabilityai/stable-diffusion-3.5-large””