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    "headline": "The Fast Event Fell Between the Frames",
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    "dek": "FastBench exposes the tradeoff between dense video sampling and the history a streaming model can retain.",
    "summary": "FastBench exposes the tradeoff between dense video sampling and the history a streaming model can retain.",
    "body_text": "FastBench contains 306 verified questions across eight domains and six capabilities, filtering out questions answerable at two frames per second and using three rounds of human inspection. Its strongest tested model, Gemini 3.5 Flash, scored 50.7%. Raising Qwen3-VL-8B sampling from two to twenty-four frames per second improved its score from 32.9% to 44.6%, but gains saturated as older history was compressed. The training-free ProactiveFrame baseline adjusts incoming rates and keeps recent dense observations alongside sparse history. It improved on sparse uniform sampling by 5.4 and 1.5 percentage points in the reported comparisons while remaining below oracle-guided focusing. Choosing when to look more closely remains part of the problem.",
    "why_it_matters": "FastBench exposes the tradeoff between dense video sampling and the history a streaming model can retain.",
    "limitations": [],
    "importance": 8,
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    "first_published_at": "2026-10-09T09:00:00.000-04:00",
    "modified_at": "2026-10-10T03:43:44.000-04:00",
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    "tags": [
      "streaming video",
      "temporal sampling",
      "video understanding"
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  "sources": [
    {
      "source_id": "source-2026-10-09-005",
      "title": "arXiv preprint 2610.12427, original v1",
      "publisher": "arXiv / submitting research authors",
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      "published_at": "2026-10-08T13:55:20.000-04:00",
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    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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    "title": "The Fast Event Fell Between the Frames",
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    "published_at": "2026-10-09T09:00:00.000-04:00",
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