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    "story_id": "mp-2026-10-14-003",
    "source_story_id": "tmp-story-chunkact-agentic-robotics",
    "edition_id": "mp-2026-10-14-morning-0096",
    "edition_url": "https://themachinepress.com/edition/2026-10-14",
    "position": 3,
    "story_type": "dispatch",
    "section": "robotics",
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    "headline": "The Robot Calls the Planner Only When the Routine Breaks",
    "slug": "the-robot-calls-the-planner-only-when-the-routine-breaks",
    "dek": "ChunkAct compiles remembered robot routines into action chunks, reserving language-model calls for decisions and failures.",
    "summary": "ChunkAct compiles remembered robot routines into action chunks, reserving language-model calls for decisions and failures.",
    "body_text": "Agentic robot systems can ask a language model to reason before every primitive action, repeatedly rereading the same history. ChunkAct's authors instead compile memory into chains of primitives that execute autonomously until a failure returns control to the planner. On LIBERO-Pro, they report a five-point success-rate gain over their agentic-robotics baseline while using 2.9 times fewer model calls, 4.4 times fewer input tokens and 2.3 times fewer output tokens. These are benchmark results, but the design isolates a practical systems idea: use expensive reasoning at decision boundaries, not at every movement.",
    "why_it_matters": "ChunkAct compiles remembered robot routines into action chunks, reserving language-model calls for decisions and failures.",
    "limitations": [
      "These are benchmark results, but the design isolates a practical systems idea: use expensive reasoning at decision boundaries, not at every movement."
    ],
    "importance": 8,
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    "first_published_at": "2026-10-14T09:00:00.000-04:00",
    "modified_at": "2026-10-14T09:00:00.000-04:00",
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        "text": "ChunkAct compiles remembered robot routines into action chunks, reserving language-model calls for decisions and failures.",
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        "qualification": "These are benchmark results, but the design isolates a practical systems idea: use expensive reasoning at decision boundaries, not at every movement."
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    "source_ids": [
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    "tags": [
      "ChunkAct",
      "agentic robotics",
      "action chunking"
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    {
      "source_id": "source-2026-10-14-003",
      "title": "arXiv preprint 2610.18874, original v1",
      "publisher": "arXiv / submitting research authors",
      "url": "https://arxiv.org/abs/2610.18874v1",
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      "source_type": "primary_research",
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      "published_at": "2026-10-13T13:59:57.000-04:00",
      "accessed_at": "2026-10-14T08:24:30.364-04:00",
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  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "The Robot Calls the Planner Only When the Routine Breaks",
    "publisher": "The Machine Press",
    "published_at": "2026-10-14T09:00:00.000-04:00",
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