{
  "id": 19191,
  "url": "https://arxiv.org/abs/2608.12788v1",
  "title": "ARAC: Benchmarking Auto-Research's Alignment and Completeness on End-to-End Researchs",
  "summary": "The rapid advancement of Auto-Research has surfaced a fundamental evaluation challenge: how can we measure the alignment, logical coherence, and evolutionary completeness of its research trajectory with human research behavior? We propose Auto-Research's Alignment and Completeness, ARAC-Bench: a Researcher-Mimicking Evaluation framework that shifts the objective from matching final answers to reproducing high-quality human research processes. The framework operates through two synergistic compon",
  "authors": "Jiale Cui, Yueyao Yuan, Kaixi Zhong, Xiaogang Xu, Jiafei Wu, Zhe Liu",
  "category": "research",
  "topics": "safety-alignment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-13T03:48:07.000Z",
  "fetched_at": "2026-08-14T05:10:49.168Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/19191",
  "original_url": "https://arxiv.org/abs/2608.12788v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}