{
  "id": 19138,
  "url": "https://arxiv.org/abs/2608.13049",
  "title": "H2R-Bench: Benchmarking Human-to-Robot Manipulation Video Generation in World Models",
  "summary": "Large-scale manipulation data is essential for robot learning, yet collecting robot demonstrations remains expensive and difficult to scale. Meanwhile, abundant egocentric human manipulation videos provide rich behavioral experiences, but transferring them across embodiments remains challenging due to differences between human hands and robotic end-effectors. Recent advances in video world models offer a promising pathway to synthesize robot-centric manipulation videos from human observations, w",
  "authors": "Dingyi Rong, Yue Shi, Chaofan Ma, Jiezhang Cao, Zongrui Wang, Zeyu Zhang",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-12T20:00:00.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "hf-daily",
  "source_name": "HuggingFace Daily Papers",
  "source_homepage": "https://huggingface.co/papers",
  "ethics_ai_record_url": "https://ethics.ai/record/19138",
  "original_url": "https://arxiv.org/abs/2608.13049",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}