Concern alignment is a new diagnostic framework that audits AI peer reviews at the level of individual concerns via match graphs to reveal gaps in detection, calibration, and prioritization beyond verdict agreement.
DIS- APERE: A dataset for discourse structure in peer review discussions
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PRISM benchmark finds LLMs match or exceed humans on isolated review dimensions like novelty verification but none achieve the balanced performance of human reviewers across depth, flaw prioritization, and constructiveness.
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What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review
Concern alignment is a new diagnostic framework that audits AI peer reviews at the level of individual concerns via match graphs to reveal gaps in detection, calibration, and prioritization beyond verdict agreement.