Human-Agent Collaborative Paper-to-Page Crafting for Under $0.1
In the quest for scientific progress, communicating research is as vital as
the discovery itself. Yet, researchers are often sidetracked by the manual,
repetitive chore of building project webpages to make their dense papers
accessible. While automation has tackled static slides and posters, the
dynamic, interactive nature of webpages has remained an unaddressed challenge.
To bridge this gap, we reframe the problem, arguing that the solution lies not
in a single command, but in a collaborative, hierarchical process. We introduce
AutoPage, a novel multi-agent system that embodies this philosophy.
AutoPage deconstructs paper-to-page creation into a coarse-to-fine pipeline
from narrative planning to multimodal content generation and interactive
rendering. To combat AI hallucination, dedicated "Checker" agents verify each
step against the source paper, while optional human checkpoints ensure the
final product aligns perfectly with the author's vision, transforming the
system from a mere tool into a powerful collaborative assistant. To rigorously
validate our approach, we also construct PageBench, the first
benchmark for this new task. Experiments show AutoPage not only generates
high-quality, visually appealing pages but does so with remarkable efficiency
in under 15 minutes for less than \0.1. Code and dataset will be released at
https://mqleet.github.io/AutoPage_ProjectPage/{Webpage}$.
68faed18f158a71c5a2f5883
Qianli Ma
claimed_verified
2025-10-24T16:01:53.631Z
6448b2f53e7b3c11be684348
https://cdn-avatars.huggingface.co/v1/production/uploads/6448b2f53e7b3c11be684348/QvlUQG3pWf8ZyEVBV6F7w.jpeg
Qianli Ma
user
Mqleet
68faed18f158a71c5a2f5884
Siyu Wang
68faed18f158a71c5a2f5885
Yilin Chen
68faed18f158a71c5a2f5886
Yinhao Tang
68faed18f158a71c5a2f5887
Yixiang Yang
68faed18f158a71c5a2f5888
Chang Guo
68faed18f158a71c5a2f5889
Bingjie Gao
68faed18f158a71c5a2f588a
Zhening Xing
68faed18f158a71c5a2f588b
Yanan Sun
68faed18f158a71c5a2f588c
Zhipeng Zhang
Human-Agent Collaborative Paper-to-Page Crafting for Under $0.1
In the quest for scientific progress, communicating research is as vital as
the discovery itself. Yet, researchers are often sidetracked by the manual,
repetitive chore of building project webpages to make their dense papers
accessible. While automation has tackled static slides and posters, the
dynamic, interactive nature of webpages has remained an unaddressed challenge.
To bridge this gap, we reframe the problem, arguing that the solution lies not
in a single command, but in a collaborative, hierarchical process. We introduce
AutoPage, a novel multi-agent system that embodies this philosophy.
AutoPage deconstructs paper-to-page creation into a coarse-to-fine pipeline
from narrative planning to multimodal content generation and interactive
rendering. To combat AI hallucination, dedicated "Checker" agents verify each
step against the source paper, while optional human checkpoints ensure the
final product aligns perfectly with the author's vision, transforming the
system from a mere tool into a powerful collaborative assistant. To rigorously
validate our approach, we also construct PageBench, the first
benchmark for this new task. Experiments show AutoPage not only generates
high-quality, visually appealing pages but does so with remarkable efficiency
in under 15 minutes for less than \0.1. Code and dataset will be released at
https://mqleet.github.io/AutoPage_ProjectPage/{Webpage}$.
AutoPage, a multi-agent system, automates the creation of interactive research webpages through a hierarchical process, ensuring high-quality and efficient results.
multi-agent system narrative planning multimodal content generation interactive rendering AI hallucination Checker agents human checkpoints PageBench benchmark