AI RESEARCH
Decoupling Scores and Text: The Politeness Principle in Peer Review
arXiv CS.LG
•
ArXi:2604.14162v1 Announce Type: cross Authors often struggle to interpret peer review feedback, deriving false hope from polite comments or feeling confused by specific low scores. To investigate this, we construct a dataset of over 30,000 ICLR 2021-2025 submissions and compare acceptance prediction performance using numerical scores versus text reviews. Our experiments reveal a significant performance gap: score-based models achieve 91% accuracy, while text-based models reach only 81% even with large language models, indicating that textual information is considerably less reliable.