AutoPage: AI System Transforms Research Papers into Interactive Web Pages

Sharing research findings effectively is just as important as making the discoveries themselves—yet many researchers spend countless hours manually building webpages to present their work. While AI has streamlined other presentation formats like slides and posters, creating dynamic, interactive web content from dense academic papers has remained an unsolved problem.

A Collaborative Approach to Content Creation#

Researchers have developed AutoPage, a multi-agent system that reimagines paper-to-page conversion as an iterative collaboration rather than a one-step automation task. Instead of treating the conversion as a single command, the system breaks it down into a structured pipeline that progresses from high-level narrative planning through content generation to final interactive rendering.

The framework introduces specialized "Checker" agents that validate each stage of the process against the original paper, preventing AI hallucinations and factual errors. Beyond algorithmic safeguards, the system also incorporates optional human checkpoints, allowing authors to review and refine outputs to match their exact vision. This transforms AutoPage from a simple automation tool into a true collaborative partner.

Performance and Benchmark Development#

The researchers created PageBench, the first benchmark specifically designed to evaluate paper-to-page generation systems. Testing shows AutoPage produces high-quality, visually polished pages with impressive speed and cost-efficiency—completing full projects in under 15 minutes for less than $0.1 per page.

The approach demonstrates that breaking complex tasks into manageable hierarchical steps, combined with verification mechanisms and human oversight, yields both superior results and practical scalability for academic publishing workflows.