{
  "id": 17974,
  "url": "https://arxiv.org/abs/2608.09873",
  "title": "Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains",
  "summary": "We introduce Sci-VBench, a comprehensive benchmark for evaluating knowledge- and reasoning-intensive video generation across scientific domains. It contains 1,253 expert-annotated examples spanning 60 subjects across four core disciplines: Natural Science, Healthcare, Humanities & Social Sciences, and Engineering. Each example requires models to generate temporally rich videos that demand scientific reasoning and knowledge-grounded synthesis, going beyond surface-level visual plausibility. We fu",
  "authors": "Diandian Zhang, Tingyu Song, Lin Fu, Zheyuan Yang, Yilun Zhao",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-09T20:00:00.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/17974",
  "original_url": "https://arxiv.org/abs/2608.09873",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}