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    "story_id": "mp-2026-08-05-016",
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    "headline": "The Diffusion Model Revised the Whole Draft",
    "slug": "the-diffusion-model-revised-the-whole-draft",
    "dek": "A plug-in decoding step improved reported math and code scores while preserving useful speed trade-offs.",
    "summary": "A plug-in decoding step improved reported math and code scores while preserving useful speed trade-offs.",
    "body_text": "A preprint lets diffusion language models generate a complete draft and then revise it bidirectionally. With LLaDA2.1, same-model draft-and-refine raised reported GSM8K accuracy from 0.848 to 0.899 and MBPP from 0.545 to 0.693; a smaller drafter with a larger refiner offered faster trade-offs rather than uniform quality parity. The evidence is limited to the tested models and benchmarks.",
    "why_it_matters": "A plug-in decoding step improved reported math and code scores while preserving useful speed trade-offs.",
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    "importance": 7,
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    "tags": [
      "diffusion language models",
      "decoding",
      "reasoning"
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    {
      "source_id": "source-2026-08-05-018",
      "title": "arXiv preprint 2608.02625",
      "publisher": "arXiv",
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    "title": "The Diffusion Model Revised the Whole Draft",
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    "published_at": "2026-08-05T09:00:00.000-04:00",
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