What Factors Should Paper-Reviewer Assignments Rely On? Community Perspectives on Issues and Ideals in Conference Peer-Review
This addresses the problem of improving peer review quality in NLP conferences by incorporating stakeholder perspectives, though it is incremental as it builds on existing matching systems.
The study surveyed the NLP community to identify common issues and perspectives on factors for paper-reviewer matching, contributing actionable recommendations for improving conferences and interpretable assignments.
Both scientific progress and individual researcher careers depend on the quality of peer review, which in turn depends on paper-reviewer matching. Surprisingly, this problem has been mostly approached as an automated recommendation problem rather than as a matter where different stakeholders (area chairs, reviewers, authors) have accumulated experience worth taking into account. We present the results of the first survey of the NLP community, identifying common issues and perspectives on what factors should be considered by paper-reviewer matching systems. This study contributes actionable recommendations for improving future NLP conferences, and desiderata for interpretable peer review assignments.