academic-plotting

To generate publication-ready figures for ML papers, provide your research context or results. The system uses Gemini to create architecture diagrams and matplotlib/seaborn for data charts, applying precise labeling and LaTeX-ready styling.

Yes, you can create architecture diagrams from a system description using Gemini. Provide your research context, and the tool extracts components and relationships to generate publication-quality diagrams with exact terminology.

To make matplotlib and seaborn charts ready for LaTeX, the tool applies publication-ready styling including appropriate fonts, color palettes, and sizing. This ensures your line charts, bar charts, and heatmaps integrate seamlessly into LaTeX documents.

The best way to visualize ablation study results is to provide the results table as context. The tool generates matplotlib/seaborn charts with publication-ready styling, ensuring precise labeling and ready-to-LaTeX outputs for your ML paper.

No external dependencies are required to generate data visualization figures. The tool internally leverages matplotlib and seaborn to produce line charts, bar charts, and heatmaps from your research context without requiring manual installation.