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  "story": {
    "story_id": "mp-2026-10-20-012",
    "source_story_id": "tmp-story-latcomm-context-packets",
    "edition_id": "mp-2026-10-20-morning-0102",
    "edition_url": "https://themachinepress.com/edition/2026-10-20",
    "position": 12,
    "story_type": "dispatch",
    "section": "infrastructure",
    "editorial_classification": "editorial",
    "headline": "One Model Sends Another a Reusable Context Packet",
    "slug": "one-model-sends-another-a-reusable-context-packet",
    "dek": "LatComm encodes shared context once, then lets a different frozen model select what to read for each question.",
    "summary": "LatComm encodes shared context once, then lets a different frozen model select what to read for each question.",
    "body_text": "Multi-model systems repeatedly pay to transmit the same text. LatComm separates encoding from reading: one frozen model compresses context into a fixed-size packet, while a different frozen receiver uses prompt-conditioned cross-attention to select relevant content. Across twelve multiple-choice datasets, the authors report up to 10.2 points higher average accuracy than single-vector baselines. On QuALITY, receiver input fell by a factor of 57 and questions were answered three times faster. The learned bridge is not universally portable, but it demonstrates context that is compact, reusable and readable by a different model.",
    "why_it_matters": "LatComm encodes shared context once, then lets a different frozen model select what to read for each question.",
    "limitations": [
      "The learned bridge is not universally portable, but it demonstrates context that is compact, reusable and readable by a different model."
    ],
    "importance": 8,
    "canonical_url": "https://themachinepress.com/story/mp-2026-10-20-012/one-model-sends-another-a-reusable-context-packet",
    "json_url": "https://themachinepress.com/story/mp-2026-10-20-012.json",
    "first_published_at": "2026-10-20T09:00:00.000-04:00",
    "modified_at": "2026-10-20T09:00:00.000-04:00",
    "content_status": "new",
    "is_carryover": false,
    "carryover_reason": null,
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        "text": "LatComm encodes shared context once, then lets a different frozen model select what to read for each question.",
        "source_ids": [
          "source-2026-10-20-012"
        ],
        "qualification": "The learned bridge is not universally portable, but it demonstrates context that is compact, reusable and readable by a different model."
      }
    ],
    "source_ids": [
      "source-2026-10-20-012"
    ],
    "tags": [
      "context compression",
      "model communication",
      "inference"
    ],
    "image_url": null,
    "corrections": []
  },
  "sources": [
    {
      "source_id": "source-2026-10-20-012",
      "title": "arXiv preprint 2610.26840, original v1",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2610.26840v1",
      "canonical_url": "https://arxiv.org/abs/2610.26840v1",
      "source_type": "primary_research",
      "is_primary_source": true,
      "published_at": "2026-10-19T13:58:41.000-04:00",
      "accessed_at": "2026-10-20T08:15:06.176-04:00",
      "supports_claim_ids": [
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  ],
  "corrections": [],
  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
  },
  "cite_this_report": {
    "title": "One Model Sends Another a Reusable Context Packet",
    "publisher": "The Machine Press",
    "published_at": "2026-10-20T09:00:00.000-04:00",
    "canonical_url": "https://themachinepress.com/story/mp-2026-10-20-012/one-model-sends-another-a-reusable-context-packet"
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