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    "story_id": "mp-2026-10-02-006",
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    "headline": "A Visual Harness Reached Perfect Action Efficiency",
    "slug": "a-visual-harness-reached-perfect-action-efficiency",
    "dek": "Lossless observation memory let one multimodal model finish all 25 public ARC-AGI-3 games.",
    "summary": "Lossless observation memory let one multimodal model finish all 25 public ARC-AGI-3 games.",
    "body_text": "VISTA preserves past visual observations in original form and lets a multimodal model retrieve and reorganize them during long-horizon reasoning. On ARC-AGI-3, the authors report that it raised Claude Opus 5.0's Relative Human Action Efficiency from 40.68 to 100, completing all 25 public games with 57.4 percent fewer actions than first-time human participants. It also improved results on three other visual-game and puzzle benchmarks. The score depends on the reported harness, model and public game set and is not a general measure of visual intelligence.",
    "why_it_matters": "Lossless observation memory let one multimodal model finish all 25 public ARC-AGI-3 games.",
    "limitations": [
      "The score depends on the reported harness, model and public game set and is not a general measure of visual intelligence."
    ],
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    "first_published_at": "2026-10-02T09:00:00.000-04:00",
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        "qualification": "The score depends on the reported harness, model and public game set and is not a general measure of visual intelligence."
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    "tags": [
      "multimodal agents",
      "visual memory",
      "interactive environments"
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  "sources": [
    {
      "source_id": "source-2026-10-02-006",
      "title": "arXiv preprint 2610.02200",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2610.02200",
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      "published_at": "2026-10-01T13:59:45.000-04:00",
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    "title": "A Visual Harness Reached Perfect Action Efficiency",
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