{
  "id": 7195,
  "url": "https://arxiv.org/abs/2604.09617v1",
  "title": "AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation",
  "summary": "Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for generating model and data cards still face three major challenges: (i) static templates, as most systems rely on fixed query templates that cannot adapt to diverse paper structures or evolving documentation requirements; (ii) information scarcity, since web-scale repositories such as Hugging Face often contain incomplete or inconsistent metadata, l",
  "authors": "Haoxuan Zhang, Ruochi Li, Zhenni Liang, Mehri Sattari, Phat Vo, Collin Qu et al.",
  "category": "research",
  "topics": "transparency",
  "orgs": "huggingface",
  "regions": null,
  "published_at": "2026-03-16T04:02:56.000Z",
  "fetched_at": "2026-07-14T16:33:03.572Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7195",
  "original_url": "https://arxiv.org/abs/2604.09617v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}