{
  "id": 3448,
  "url": "https://arxiv.org/abs/2605.30995v2",
  "title": "Traceable by Design: An LLM Pipeline and Dashboard for EU Regulatory Consultation Analysis",
  "summary": "Public consultations generate large volumes of data in the form of stakeholder submissions that are practically unfeasible to analyse manually. We present an end-to-end LLM-based pipeline and interactive dashboard for structured topic extraction from regulatory consultation submissions, demonstrated on the European Commission's Digital Fairness Act (DFA) public call for evidence as a case study. The system processes raw PDF attachments and web-form responses, extracts topic annotations, and grou",
  "authors": "Thales Bertaglia, Haoyang Gui, Catalina Goanta, Gerasimos Spanakis",
  "category": "research",
  "topics": "bias-fairness,regulation",
  "orgs": null,
  "regions": "eu",
  "published_at": "2026-05-29T08:29:00.000Z",
  "fetched_at": "2026-07-14T16:30:14.371Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3448",
  "original_url": "https://arxiv.org/abs/2605.30995v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}