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    "headline": "More Human Examples Made the Machine Distribution Harder to See",
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    "dek": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
    "summary": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
    "body_text": "Under stated mixing and stability assumptions, the paper derives a convergence rate and describes how the needed human samples and paraphrasing rounds scale with the target error. The result characterizes a strategic evasion process in a controlled multi-sample setting; it does not prove that all AI text is presently undetectable.",
    "why_it_matters": "A theoretical analysis shows repeated paraphrasing can move machine-written responses toward an empirical human-writing distribution.",
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      "The result characterizes a strategic evasion process in a controlled multi-sample setting; it does not prove that all AI text is presently undetectable."
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    "tags": [
      "AI text detection",
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      "title": "arXiv preprint 2608.26797",
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    "title": "More Human Examples Made the Machine Distribution Harder to See",
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