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    "story_id": "mp-2026-08-30-004",
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    "headline": "The Paraphrase Kept What the Seed Forgot",
    "slug": "the-paraphrase-kept-what-the-seed-forgot",
    "dek": "GRAPHSU expands deletion pressure from named forget examples into neighboring support routes.",
    "summary": "GRAPHSU expands deletion pressure from named forget examples into neighboring support routes.",
    "body_text": "The method builds a weighted graph around aliases, paraphrases and connected training samples, then applies graded forgetting to high-risk neighbors. On TOFU and PISTOL with GPT-2 Medium and Llama-3.2-3B-Instruct, the authors report up to a 49.5-percentage-point leakage reduction over a matched seed-only baseline while retaining feasible utility. Both benchmarks are controlled evaluation settings, so enterprise deletion claims still need domain-specific testing.",
    "why_it_matters": "GRAPHSU expands deletion pressure from named forget examples into neighboring support routes.",
    "limitations": [
      "On TOFU and PISTOL with GPT-2 Medium and Llama-3.2-3B-Instruct, the authors report up to a 49.5-percentage-point leakage reduction over a matched seed-only baseline while retaining feasible utility."
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    "first_published_at": "2026-08-30T09:00:00.000-04:00",
    "modified_at": "2026-08-30T09:00:00.000-04:00",
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        "qualification": "On TOFU and PISTOL with GPT-2 Medium and Llama-3.2-3B-Instruct, the authors report up to a 49.5-percentage-point leakage reduction over a matched seed-only baseline while retaining feasible utility."
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    "tags": [
      "machine unlearning",
      "privacy",
      "language models"
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  "sources": [
    {
      "source_id": "source-2026-08-30-004",
      "title": "arXiv preprint 2608.26743",
      "publisher": "arXiv",
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      "published_at": "2026-08-27T03:33:17.000-04:00",
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  "cite_this_report": {
    "title": "The Paraphrase Kept What the Seed Forgot",
    "publisher": "The Machine Press",
    "published_at": "2026-08-30T09:00:00.000-04:00",
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