Would a new result in pre-print be considered by reviewers? [D]

2026-05-18 · Source: Machine Learning · Field: Science & Research — Research Methodology & Innovation, Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

A discussion among researchers addresses the ethical and procedural dilemma of reviewing a submitted paper when an updated preprint version, addressing significant omissions, is available on arXiv. The core question is whether reviewers should acknowledge and consider the unpublished, updated preprint or strictly evaluate only the submitted manuscript. One perspective argues that in fields like CS/ML/AI/NLP, reviewers typically expect unpublished works to be cited and considered, emphasizing the pursuit of scientific truth over strict process adherence. This view suggests that while authors are at fault for submitting incomplete work, reviewers should still point out the omission and allow authors to update the camera-ready version, unless suspicious intent is perceived.

Key takeaway

For research scientists reviewing papers, if you encounter an "elephant in the room" addressed in a newer preprint, you should acknowledge it. Mention the omission in your review, citing the updated arXiv version. This approach prioritizes scientific completeness and allows authors to integrate their latest findings into the camera-ready version, ensuring the final publication reflects the most current and thorough work.

Key insights

Reviewers should consider updated preprints to prioritize scientific truth over strict adherence to submitted versions.

Principles

• Scientific truth outweighs process.
• Unpublished works merit consideration.

In practice

• Cite relevant preprints in submissions.
• Address known omissions proactively.

Topics

• Academic Peer Review
• Pre-print Publications
• arXiv
• Research Ethics
• Manuscript Submission

Best for: AI Scientist, Research Scientist, AI Student

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning.