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    "story_id": "mp-2026-10-24-027",
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    "headline": "A Memory Can Be Valuable Even When It Does Not Store the Answer",
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    "dek": "A decision-theoretic framework tracks what history preserves, what bounded agents can use and what expensive recovery remains possible.",
    "summary": "A decision-theoretic framework tracks what history preserves, what bounded agents can use and what expensive recovery remains possible.",
    "body_text": "The paper measures memory in units of avoided task loss rather than raw recall. It follows value from history into persistent state, operational use and later recovery or revision, with frontiers that make risk and cost explicit. Minimal counterexamples separate information timing, retrieval access, component interaction, feedback and demand uncertainty. One striking case shows that a pointer carrying no mutual information about the answer can still reduce the cost of exact recovery. Dataset and longitudinal diagnostics illustrate how preservation, use and evaluation can each fail. This is a framework for reasoning about memory value, not a universal ranking of memory architectures.",
    "why_it_matters": "A decision-theoretic framework tracks what history preserves, what bounded agents can use and what expensive recovery remains possible.",
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      "This is a framework for reasoning about memory value, not a universal ranking of memory architectures."
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    "tags": [
      "agent memory",
      "decision theory",
      "evaluation"
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  "sources": [
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      "source_id": "source-2026-10-24-016",
      "title": "arXiv preprint 2610.31303, original v1",
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      "published_at": "2026-10-22T10:01:31.000-04:00",
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    "title": "A Memory Can Be Valuable Even When It Does Not Store the Answer",
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