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PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress
Autoresearch agents are reshaping the research ecosystem, but they can also let flawed claims enter the literature at scale. Human advisors catch such issues in drafts through careful, traceable feedback, yet advisor-style assessment requires extensive manual effort and does not scale. To shift automated paper assessment from a judge to a diagnostician, we introduce PaperDoctor, an agent framework for pre-submission feedback with three key innovations. First, a holistic hierarchical framework evaluates writing, layout, references, code, theory, prior work, and experiments through three layers:
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T11:08:11.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.