MERIT: Matching Expertise via Rubric-Informed Training for Reviewer Assignment

Excerpt

arXiv:2605.27865v2 Announce Type: replace Abstract: Matching submissions with suitable reviewers at scale is a growing challenge for major venues, yet existing approaches either rely on coarse proxy signals that conflate general relatedness with true suitability, or require expensive human annotations that are difficult to scale for training. We propose MERIT, a two-stage framework that bridges this gap by converting criterion-level expertise matching into scalable suitability supervision. In th