Poster
in
Workshop: CODEML: Championing Open-source DEvelopment in Machine Learning
Swizz: One-Liner Figures, LaTeX Tables, and Flexible Layouts for Scientific Papers
Lars Quaedvlieg · Andrea Miele · Caglar Gulcehre
Producing publication-quality visualizations and tables for machine learning papers is often tedious, time-consuming, and prone to inconsistencies. We introduce Swizz, a lightweight Python library designed specifically for researchers to effortlessly generate elegant figures, LaTeX-ready tables, and customizable figure layouts with minimal code. Swizz enables one-liner creation of consistent, conference-ready visualizations, including advanced plots and multilevel tables, and provides intuitive, composable layouts to simplify complex figure arrangements. Its automated styling and built-in visual gallery facilitate rapid experimentation, allowing researchers to focus more on research and less on formatting. Swizz is publicly available, easy to integrate into existing workflows, and themed for major machine learning publication venues. Swizz is open source (MIT) and is available on GitHub and PyPI.