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    "headline": "Private Network Counts Reach the Noninteractive Limit",
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    "dek": "A local node-differential-privacy algorithm counts any constant-size template subgraph with near-optimal additive error.",
    "summary": "A local node-differential-privacy algorithm counts any constant-size template subgraph with near-optimal additive error.",
    "body_text": "The matching lower bound establishes the first polynomial-in-n separation between central and local node privacy for accuracy on all input graphs. The result is theoretical and expands beyond prior degree-distribution statistics; it is not a deployment benchmark.",
    "why_it_matters": "A local node-differential-privacy algorithm counts any constant-size template subgraph with near-optimal additive error.",
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      "title": "arXiv preprint 2610.22278, original v1",
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    "title": "Private Network Counts Reach the Noninteractive Limit",
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