- Who it helps
- Researchers evaluating manuscript feedback and automated review systems.
- Availability
- November 1 preprint describes PaperTrajectory-2026; dataset and evaluation execution were not checked.
What was compared
The study examines 6,959 paper trajectories across five AI conferences, using automatic change annotations and eight AI reviewers. Most annotated major improvements leave scores unchanged; agreement about score direction is weak.
User framing changes the result
The authors report that a short negative user opinion can erase or reverse some score gains. This supports checking whether feedback follows manuscript evidence. It does not establish a dependable automated acceptance decision.
What you can do
- Read the linked primary evidence and its access limits before planning a trial. Open reference ↗
Where the evidence stops
Abstract read November 6. Automatic annotations and reviewer-specific settings limit generalization; results were not reproduced.
Sources read. Sources read November 6, 2026 UTC. No third-party project, model inference or complete product workflow was executed.
Sources & further reading
Paper · paper
AI paper reviewers can miss substantial revisions ↗
Primary page read November 6. Claims were checked against the page; the workflow was not executed.
PaperTrajectory authors · page checked 2026-11-06
Coverage note: Original YouTube demonstrations and independent cross-platform attention were not established. No end-to-end workflow was executed.
The record over time (1)
Dated source checks and published explanations. An observation date can differ from the original release date.
- · Added to Current
A paper-revision study finds that AI review scores often stay unchanged after major improvements.