Academic Plotting for ML Papers
技能 已验证 活跃Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
Automate the creation of publication-quality figures for ML/AI conference papers, saving researchers significant time and ensuring visual consistency and correctness.
功能
- Generate architecture diagrams via Gemini AI
- Auto-select chart types based on data
- Create data-driven figures with matplotlib/seaborn
- Apply venue-specific styling (color palettes, fonts, sizes)
- Highlight 'our method' in data visualizations
使用场景
- Creating system architecture diagrams for a conference paper.
- Generating plots for experimental results (e.g., training curves, ablation studies).
- Ensuring figures meet the visual and formatting standards of top ML venues.
- Quickly producing multiple figures for a paper using descriptive text or data.
非目标
- Writing the entire ML paper (though it complements the 'ML Paper Writing' skill).
- Generating interactive plots or web-based visualizations.
- Performing complex statistical analysis beyond basic plotting.
- Replacing manual plot customization for highly niche or artistic requirements.
工作流
- User provides research context or data.
- Skill extracts relevant entities, relationships, or data dimensions.
- Skill selects appropriate figure type (diagram or data chart) and style.
- Skill generates figure using Gemini or matplotlib/seaborn.
- Skill saves figure as PDF and PNG with appropriate naming conventions.
实践
- Visualization Best Practices
- Diagram Generation
- Data Visualization
- Publication Standards
先决条件
- Python 3.8+
- Matplotlib >= 3.8.0
- Seaborn >= 0.13.0
- Numpy
- google-genai >= 1.0.0
- GEMINI_API_KEY environment variable set
Execution
- info:Pinned dependenciesThe SKILL.md lists dependencies (matplotlib>=3.8.0, etc.) but does not include a lockfile or explicit pinning for the Python environment, which could lead to versioning issues.
安装
请先添加 Marketplace
/plugin marketplace add Orchestra-Research/AI-Research-SKILLs/plugin install AI-Research-SKILLs@ai-research-skills质量评分
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