# Automated Generation of Illustrations for Synthetic Geometry Proofs

arXiv: https://arxiv.org/abs/2201.00540 · HTML: https://mlsanity.com/paper/2201.00540/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jan 2022.

## Built on by (most cited first, 2 of 2)

- [A Survey of Deep Learning for Geometry Problem Solving](https://mlsanity.com/paper/2507.11936/) (2025)
- [Towards Automated Readable Proofs of Ruler and Compass Constructions](https://mlsanity.com/paper/2401.13700/) (2024)

## Abstract (arXiv)

We report on a new, simple, modular, and flexible approach for automated generation of illustrations for (readable) synthetic geometry proofs. The underlying proofs are generated using the Larus automated prover for coherent logic, and corresponding illustrations are generated in the GCLC language. Animated illustrations are also supported.