PeerPrism: Peer Evaluation Expertise vs Review-writing AI
Large Language Models (LLMs) are increasingly used in scientific peer review, assisting with drafting, rewriting, expansion, and refinement. However, existing peer-review LLM detection methods largely treat authorship as a binary problem-human vs. AI-without accounting for the hybrid nature of modern review workflows. In practice, evaluative ideas and surface realization may originate from different sources, creating a spectrum of human-AI collaboration. In this work, we introduce PeerPrism, a large-scale benchmark of 20,690 peer reviews explicitly designed to disentangle idea provenance from text provenance. We construct controlled generation regimes spanning fully human, fully synthetic...
| Authors | Soroush Sadeghian, Alireza Daqiq, Radin Cheraghi et al. |
|---|---|
| Primary category | cs.CL |
| Published | 16 April 2026 |
| Last updated at source | 16 April 2026 |
Models and datasets referencing this paper
- Reviewerly/PeerPrismDataset
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