# COrigami: An AI Pipeline for Co-Designing Flat-Foldable Visually Recognisable Origami

arXiv: https://arxiv.org/abs/2606.26299 · HTML: https://mlsanity.com/paper/2606.26299/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 42 references that are in the map.
- First posted on arXiv 24 Jun 2026.

## Builds on (most cited first, 13 of 13)

- [Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities](https://mlsanity.com/paper/2507.06261/) (2025)
- [From System 1 to System 2: A Survey of Reasoning Large Language Models](https://mlsanity.com/paper/2502.17419/) (2025)
- [OmniSVG: A Unified Scalable Vector Graphics Generation Model](https://mlsanity.com/paper/2504.06263/) (2025)
- [Empowering LLMs to Understand and Generate Complex Vector Graphics](https://mlsanity.com/paper/2412.11102/) (2024)
- [Generating Physically Stable and Buildable Brick Structures from Text](https://mlsanity.com/paper/2505.05469/) (2025)
- [Generating Creative Chess Puzzles](https://mlsanity.com/paper/2510.23881/) (2025)
- [ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints](https://mlsanity.com/paper/2511.18450/) (2025)
- [Agentic AI in the Software Development Lifecycle: Architecture, Empirical Evidence, and the Reshaping of Software Engineering](https://mlsanity.com/paper/2604.26275/) (2026)
- [Can AI Understand the Language of Origami?](https://mlsanity.com/paper/2603.13856/) (2026)
- [Evaluating In Silico Creativity: An Expert Review of AI Chess Compositions](https://mlsanity.com/paper/2510.23772/) (2025)
- [Evolution & Foundation: AI Shares Creative Control](https://mlsanity.com/paper/2606.16849/) (2026)
- [Folding a Paper Strip to Minimize Thickness](https://mlsanity.com/paper/1411.6371/) (2014)
- [STEP-LLM: Generating CAD STEP Models from Natural Language with Large Language Models](https://mlsanity.com/paper/2601.12641/) (2026)

## Abstract (arXiv)

While generative AI has achieved remarkable success in solving problems with verifiable solutions, generating physical art that satisfies both strict geometric constraints and subjective visual aesthetics remains a challenge. This paper presents an approach to tackle these difficulties in the domain of computational origami, a mathematically rigid environment that grounds artistic design within the equations of flat foldability. We present COrigami, an end-to-end AI-driven pipeline that assists the design cycle by generating crease patterns from natural language. Our pipeline involves generating a semantic stick figure, computing a base packing, solving for a flat-foldable crease pattern, shaping the flat-folded crease pattern, and refining the generated model using reinforcement learning driven by an autonomous aesthetic evaluation loop. Our system acts as a highly effective collaborative assistant, generating structural starting points that human artists can further expand and shape. By integrating algorithmic optimisation with autonomous aesthetic critique, this work demonstrates how AI systems can satisfy multi-objective physical constraints to enable reliable, mathematically grounded co-creativity.