Evaluating the Impact of Reviewer Guideline Design on LLM-Based Automated Peer Review
Peer review is an essential process in scientific research, yet the growing workload has made its automation increasingly necessary. In this study, we analyze how different types of reviewer guidelines, such as official conference guidelines and reviewer-imitating ones generated from high-quality human reviews using LLMs, affect automated peer review. Our experiments show that official conference guidelines produce review results most consistent with human judgments, suggesting that evaluation criteria refined through conference practice serve as effective guidance for automated reviewing as well. In contrast, reviewer-imitating guidelines were generally less effective than official confe...
| Authors | Haowen Li, Yoichi Ishibashi, Masafumi Oyamada |
|---|---|
| Primary category | cs.CL |
| Published | 16 May 2026 |
| Last updated at source | 16 May 2026 |
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