mlsanityData to 7 Oct 2026

What Factors Should Paper-Reviewer Assignments Rely On? Community Perspectives on Issues and Ideals in Conference Peer-Review

arXiv 2205.01005 ↗First posted 2 May 2022cs.CLcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 8 of its 36 references that are in the map. First posted on arXiv 2 May 2022.

Builds on

8 of 36 references.

References · 8

  1. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 426
  2. 2019Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasetscited by 173
  3. 2021Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experimentcited by 49
  4. 2020What Can We Do to Improve Peer Review in NLP?cited by 32
  5. 2018PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Reviewcited by 30
  6. 2019Simple and Effective Paraphrastic Similarity from Parallel Translationscited by 25
  7. 2018A Study of Position Bias in Digital Library Recommender Systemscited by 13
  8. 2021Combating Collusion Rings is Hard but Possiblecited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 1.

4 papers.