{
  "id": 11306,
  "url": "https://arxiv.org/abs/2607.14047v2",
  "title": "Zero2Skill: Bootstrapping Robot Skills through Autonomous Data Collection, Training, and Deployment",
  "summary": "Autonomous data collection governs the volume and quality of real-world trajectories for manipulation policy learning. Existing pipelines reduce human effort via self-resetting, VLM verification, or language-guided correction, yet episode-scoped fixes must be reissued whenever the same failure recurs, so oversight cost grows with session length rather than with the number of distinct problems. We present Zero2Skill, a human-robot symbiotic agentic system in which corrections are retained and reu",
  "authors": "Boyuan Wang, Zhenyuan Zhang, Zhiqin Yang, Peijun Gu, Shuya Wang, Xiaofeng Wang, Xianghui Ze, Yifan Chang, Guosheng Zhao, Jiangnan Shao, Guan Huang, Hengyu Liu, Yonggang Zhang, Wei Xue, Chunyuan Guan, Chenglin Pu, Yike Guo, Xingang Wang, Zheng Zhu",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-15T17:16:24.000Z",
  "fetched_at": "2026-07-17T05:10:53.887Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/11306",
  "original_url": "https://arxiv.org/abs/2607.14047v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}