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paper-figure

Generate publication-quality figures and LaTeX tables from experiment JSON or CSV data.

2|Updated Aug 12, 2025
Search Tags:#matplotlib#research paper#publication graphics#academic visualization#paper figures#latex tables#experiment plots
One-click install
npx skills add https://github.com/goupup-ai/miccai25 --skill paper-figure-goupup-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-figure
Source: https://github.com/goupup-ai/miccai25/tree/main/ARIS/skills/paper-figure
Command: npx skills add https://github.com/goupup-ai/miccai25 --skill paper-figure-goupup-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually creating publication-quality figures and tables for academic papers is time-consuming, requires specialized plotting expertise, and often produces inconsistent formatting that fails to meet top-tier conference submission standards.

Core Features & Use Cases

  • Automated data visualization: Generates line plots, bar charts, scatter plots, heatmaps, box/violin plots, and multi-panel subfigures directly from experiment JSON or CSV data.
  • LaTeX table generation: Creates print-ready comparison tables for method benchmarks and ablation studies, formatted for direct inclusion in LaTeX manuscripts.
  • Consistent publication styling: Enforces vector PDF output, conference-matched serif fonts, colorblind-safe color palettes, and proper sizing for single-column or full-width placement.
  • Use case: For a MICCAI 2025 vertebrae segmentation paper, use this skill to automatically generate training loss curves, state-of-the-art comparison bar charts, and ablation study tables from experiment result files, all formatted to meet conference requirements.

Quick Start

Use the paper-figure skill to generate all publication-ready figures and LaTeX include snippets from the experiment data in your project's figures/ directory and the figure plan in PAPER_PLAN.md.

Frequently Asked Questions about paper-figure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate publication-ready paper figures from experiment data?▼

Generate publication-ready paper figures by feeding raw experiment JSON or CSV files into an automated plotting workflow that outputs vector PDFs, training curves, and comparison charts formatted for top-tier machine learning conferences. It handles sizing and styling automatically.

Can I create LaTeX tables for ablation studies from CSV results?▼

Yes, you can create LaTeX tables for ablation studies from CSV results by using automated table generation to produce print-ready comparison tables formatted for direct inclusion in LaTeX manuscripts.

Does this approach support colorblind-safe palettes for academic visualization?▼

Yes, academic visualization outputs enforce colorblind-safe color palettes alongside conference-matched serif fonts and single-column or full-width sizing to ensure compliance with academic publication standards.

What is the best way to automate experiment plots for a CVPR or NeurIPS paper?▼

Automate experiment plots for CVPR or NeurIPS papers by processing raw experiment data through a script that generates reproducible training loss curves, method comparison bar charts, and scatter plots with vector PDF output.

Do I need matplotlib expertise to build multi-panel subfigures for research papers?▼

No, you do not need matplotlib expertise to build multi-panel subfigures for research papers because the automated workflow handles the layout, styling, and reproducible generation scripts directly from your experiment data files.

Are there limitations when generating paper figures for conferences not matching MICCAI or NeurIPS standards?▼

The workflow is specifically optimized for machine learning conference standards like MICCAI, CVPR, and NeurIPS, so using it for journals or conferences with significantly different formatting requirements may require manual adjustments to the output sizing and fonts.

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