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    "story_id": "mp-2026-08-10-007",
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    "headline": "The Model Learned Where to Be Creative",
    "slug": "the-model-learned-where-to-be-creative",
    "dek": "CreativeInstruct marks spans where a post-trained language model should recover diversity without abandoning answer quality.",
    "summary": "CreativeInstruct marks spans where a post-trained language model should recover diversity without abandoning answer quality.",
    "body_text": "The method trains models to insert special creativity spans, aiming to recover base-model diversity while retaining post-training quality. It also introduces a graph-edit metric for narrative structure. In the authors' human study, annotators preferred CreativeInstruct outputs as more creative than post-trained baselines in 70.3 percent of comparisons; reinforcement learning from the creative checkpoint also improved reported AMC and MATH results. These are preprint evaluations, not a general measure of creativity.",
    "why_it_matters": "CreativeInstruct marks spans where a post-trained language model should recover diversity without abandoning answer quality.",
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      "These are preprint evaluations, not a general measure of creativity."
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    "first_published_at": "2026-08-10T09:00:00.000-04:00",
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        "text": "CreativeInstruct marks spans where a post-trained language model should recover diversity without abandoning answer quality.",
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        "qualification": "These are preprint evaluations, not a general measure of creativity."
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    "tags": [
      "language models",
      "creativity",
      "instruction tuning"
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  "sources": [
    {
      "source_id": "source-2026-08-10-007",
      "title": "arXiv preprint 2608.07460",
      "publisher": "arXiv",
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      "published_at": "2026-08-07T13:00:00.000-04:00",
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  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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    "title": "The Model Learned Where to Be Creative",
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