Rxiv-Maker: An Automated Template Engine for Streamlined Scientific Publications

2025-06-26

AI Summary

Researchers face challenges in academic writing—including verbose LaTeX coding, poor version control, low collaborative efficiency, and irreproducible results. To address these, this paper proposes a GitHub-based automated manuscript generation framework. It adopts Markdown as the source format and integrates automated LaTeX compilation, programmatic figure generation, and continuous integration (CI) pipelines to enable end-to-end, traceable, and reproducible scientific writing—from raw data to publication-ready PDF. Crucially, the framework redefines manuscripts as “executable outputs,” unifying version control, computational provenance tracking, and dynamic content updating. Evaluated in computational biology and microscopic image analysis workflows, the framework significantly improves collaborative productivity and adherence to open science principles, while supporting high-quality, fully reproducible scholarly publishing.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Humans and AI: Crowd Sourcing and Human Computation
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity

Abstract

Scientific publishing increasingly relies on preprint servers for rapid dissemination, yet researchers often struggle with manuscript preparation and quality control. Here we present Rxiv-Maker, a GitHub-native framework that converts markdown content to publication-ready PDFs through automated LaTeX processing. The system addresses reproducibility challenges in computational biology and imaging research by treating manuscripts as executable outputs rather than static documents. Rxiv-Maker integrates version control workflows with automated build environments, enabling collaborative manuscript development whilst maintaining computational provenance. The framework supports programmatic figure generation, essential for microscopy and image analysis workflows where visualisations must reflect current data and processing algorithms. This manuscript, generated entirely using Rxiv-Maker, demonstrates the system's capacity to bridge accessible authoring with professional typesetting, offering researchers a transparent pathway from data to publication that aligns with open science principles.

Problem

• Simplifies manuscript preparation without LaTeX expertise
• Automates Markdown-to-LaTeX conversion for publication-ready PDFs
• Integrates dynamic figure generation and version control

Innovation

• Converts Markdown to LaTeX automatically
• Generates dynamic version-controlled PDFs
• Executes Python/R for live figure updates