{
  "id": 726,
  "url": "https://arxiv.org/abs/2606.22706v1",
  "title": "Safety-Aware Evaluation of LLM-Generated Driver Intervention Messages through Multi-Task Risk Fusion",
  "summary": "Existing driver intervention systems rely on auditory alerts and fixed templates, failing to leverage multi-task recognition outputs. General-purpose metrics such as BLEU and BERTScore cannot capture intervention-specific quality dimensions including risk-urgency alignment, cognitive load, and driver acceptability. In this paper, we propose the Driver Safety-Aware Intervention Score (DSAIS), a domain-specific metric evaluating five dimensions through a hybrid architecture combining lightweight r",
  "authors": "Keito Inoshita",
  "category": "research",
  "topics": "safety-alignment,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-21T22:50:55.000Z",
  "fetched_at": "2026-07-14T14:14:46.033Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/726",
  "original_url": "https://arxiv.org/abs/2606.22706v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}