{
  "id": 785,
  "url": "https://arxiv.org/abs/2606.20897v1",
  "title": "PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality",
  "summary": "As academic submissions grow, the traditional peer review process struggles to keep up, raising concerns about quality and fairness. A trend of using large language models (LLMs) for assistance has emerged. In this work, we take a critical step toward improving the quality of LLM-generated reviews. We propose the PeerCheck framework, which investigates LLM-human review differences (RQ1) and explores methods to improve LLM-generated review quality (RQ2). We first analyzed the human-written review",
  "authors": "Zeyuan Chen, Ziqing Yang, Yihan Ma, Michael Backes, Yang Zhang",
  "category": "research",
  "topics": "bias-fairness,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-18T19:45:28.000Z",
  "fetched_at": "2026-07-14T14:14:46.036Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/785",
  "original_url": "https://arxiv.org/abs/2606.20897v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}