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    "story_id": "mp-2026-10-18-027",
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    "edition_id": "mp-2026-10-18-morning-0100",
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    "position": 16,
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    "headline": "Recall Is Not the Same as Reusable Knowledge",
    "slug": "recall-is-not-the-same-as-reusable-knowledge",
    "dek": "Across eleven models and seventy relations, linear readability before fine-tuning predicts whether a newly labeled relation generalizes.",
    "summary": "Across eleven models and seventy relations, linear readability before fine-tuning predicts whether a newly labeled relation generalizes.",
    "body_text": "A model may recall a fact without representing it in a form that supports new learning. The authors create arbitrary relabelings of known relations—such as mapping continents to animal words—fine-tune on a subset of subjects and test whether the new labels transfer to held-out subjects sharing the original answer. Across eleven language models and seventy relations, the linear readability of the original relation before fine-tuning predicted later generalization, with within-model correlations from 0.87 to 0.92. The association survived controls for recall accuracy, subject frequency and training-set structure. The study uses constructed relations, but it cleanly separates stored facts from representations that can be repurposed.",
    "why_it_matters": "Across eleven models and seventy relations, linear readability before fine-tuning predicts whether a newly labeled relation generalizes.",
    "limitations": [],
    "importance": 8,
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    "first_published_at": "2026-10-18T09:00:00.000-04:00",
    "modified_at": "2026-10-18T09:00:00.000-04:00",
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        "text": "Across eleven models and seventy relations, linear readability before fine-tuning predicts whether a newly labeled relation generalizes.",
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    "tags": [
      "language models",
      "fine-tuning",
      "representations"
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    "image_url": null,
    "corrections": []
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  "sources": [
    {
      "source_id": "source-2026-10-18-016",
      "title": "arXiv preprint 2610.22300, original v1",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2610.22300v1",
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      "source_type": "primary_research",
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      "published_at": "2026-10-15T13:47:52.000-04:00",
      "accessed_at": "2026-10-18T08:23:52.920-04:00",
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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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  "cite_this_report": {
    "title": "Recall Is Not the Same as Reusable Knowledge",
    "publisher": "The Machine Press",
    "published_at": "2026-10-18T09:00:00.000-04:00",
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