An AI agent for auditing reproducibility in conference papers
In brief
- An AI agent collaborates with authors to audit reproducibility of scientific papers.
- A structured GitHub workflow enables clarifications and corrections in a loop.
- 20 reproducibility issues detected and resolved across 36 analyzed papers.
A collaborative system using an AI agent and author-in-the-loop checks audits the reproducibility of conference submissions. The approach combines structured checklists and a GitHub workflow to identify and fix reproducibility issues. The study shows this method detected and resolved 20 problems across 36 analyzed papers.
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