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Measured Coupling for Parallel Decoding in Diffusion Language Models

Nov 5, 2026 Source ↗

Key Insights

Diffusion language models can write many tokens per step, but must choose which tokens are safe to commit together.
Mean-field decoding penalizes pairs of positions whose predictions look alike.
We re.

DataOps

Cite this synthesis DOI: 10.48550/arXiv.2611.08307 ↗

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@misc{ acaciadata-research-measured-coupling-for-parallel-decoding-in-diffusion-languag,
  title = { Measured Coupling for Parallel Decoding in Diffusion Language Models },
  author = { Leszek },
  year = { 2026 },
  doi = { 10.48550/arXiv.2611.08307 },
  url = { http://arxiv.org/abs/2611.08307v1 },
  note = {Summarized and classified by AcaciaFund}
}

TY  - GEN
TI  - Measured Coupling for Parallel Decoding in Diffusion Language Models
AU  - Leszek
PY  - 2026
DO  - 10.48550/arXiv.2611.08307
UR  - http://arxiv.org/abs/2611.08307v1
ER  -

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Overview

Diffusion language models can write many tokens per step, but must choose which tokens are safe to commit together. Mean-field decoding penalizes pairs of positions whose predictions look alike. We re

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distributed-systems dataops

DataOps

SQI 0.750