Paper2Web: Let's Make Your Paper Alive (francischen3.github.io)

Researchers introduced PAPER2WEB, a new task and system for turning full academic papers into interactive, layout-aware webpages that preserve scholarly rigor while enabling multimedia, responsiveness, and richer navigation. Unlike recent tools such as Paper2Poster and PresentAgent—which produce visual summaries or presentations but often lose fine-grained content or neglect embedded media—PAPER2WEB targets full-paper fidelity and usability, addressing common problems like disordered HTML rendering, static content, and lack of interactivity that limit modern dissemination and engagement. The core technical contribution is PWAGENT, a multi-agent generation pipeline driven by a Model Context Protocol (MCP). Agents coordinate structured asset parsing (text, figures, tables, equations), intelligent layout allocation for visual balance and accessibility, and iterative refinement loops to improve fidelity and usability. According to the authors, this approach yields web outputs that score highly on content fidelity and user-facing metrics, even outperforming human-designed templates in key areas. For the AI/ML community, PAPER2WEB promises easier sharing, reproducibility, and discovery—automating conversion of PDFs into responsive, media-rich webpages—and suggests broader applications for multi-agent orchestration and layout-aware content generation in scholarly publishing.