ScholarPeer introduces a multi-agent system with historian, scout, and Q&A agents that achieves higher win rates than prior models when evaluated on 1800 ICLR submissions for automated peer review tasks.
Regression Precision:Generative approaches (GANs, Diffusion) offer high-fidelity counterfactuals but suffer from training instability
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.MA 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review
ScholarPeer introduces a multi-agent system with historian, scout, and Q&A agents that achieves higher win rates than prior models when evaluated on 1800 ICLR submissions for automated peer review tasks.