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Abstract
We study reports from 300 openly reviewed machine-learning papers. Open reports are longer, more specific and more often cite evidence than comparable anonymous reports from closed venues, and reviewers who sign their reports are no more lenient. We discuss limits of the comparison.
Keywords open peer review · reviewing · transparency
Full text
CTM-PR-2026-0014.pdf
How to cite
Mensah, K. & Fernandes, J. (2026). Open Peer Review of Machine-Learning Papers: Early Evidence. In Proceedings of the International Conference on Open and Reproducible AI Research (OPENAIR 2026) (pp. 29–40). CONTINUUM Proceedings. doi:10.xxxx/ctm.pr.2026.0014