Human-Agent Collaborative Paper-to-Page Crafting for Under $0.1
Authors: name: Qianli Ma, name: Siyu Wang, name: Yilin Chen, name: Yinhao Tang, name: Yixiang Yang, name: Chang Guo, name: Bingjie Gao, name: Zhening Xing, name: Yanan Sun, name: Zhipeng Zhang
Organization: AutoLab

In the quest for scientific progress, communicating research is as vital as
the discovery itself. Yet, researchers are often sidetracked by the manual,
repetitive chore of building project webpages to make their dense papers
accessible. While automation has tackled static slides and posters, the
dynamic, interactive nature of webpages has remained an unaddressed challenge.
To bridge this gap, we reframe the problem, arguing that the solution lies not
in a single command, but in a collaborative, hierarchical process. We introduce
AutoPage, a novel multi-agent system that embodies this philosophy.
AutoPage deconstructs paper-to-page creation into a coarse-to-fine pipeline
from narrative planning to multimodal content generation and interactive
rendering. To combat AI hallucination, dedicated "Checker" agents verify each
step against the source paper, while optional human checkpoints ensure the
final product aligns perfectly with the author's vision, transforming the
system from a mere tool into a powerful collaborative assistant. To rigorously
validate our approach, we also construct PageBench, the first
benchmark for this new task. Experiments show AutoPage not only generates
high-quality, visually appealing pages but does so with remarkable efficiency
in under 15 minutes for less than \0.1. Code and dataset will be released at
https://mqleet.github.io/AutoPage_ProjectPage/{Webpage}$.