# ChatPattern: Layout Pattern Customization via Natural Language

arXiv: https://arxiv.org/abs/2403.15434 · HTML: https://mlsanity.com/paper/2403.15434/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 20 references that are in the map.
- First posted on arXiv 15 Mar 2024.

## Builds on (most cited first, 8 of 8)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Denoising Diffusion Implicit Models](https://mlsanity.com/paper/2010.02502/) (2020)
- [Structured Denoising Diffusion Models in Discrete State-Spaces](https://mlsanity.com/paper/2107.03006/) (2021)
- [RePaint: Inpainting using Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2201.09865/) (2022)
- [DiffPattern: Layout Pattern Generation via Discrete Diffusion](https://mlsanity.com/paper/2303.13060/) (2023)
- [AdaOPC: A Self-Adaptive Mask Optimization Framework For Real Design Patterns](https://mlsanity.com/paper/2303.12723/) (2023)
- [Layout decomposition for triple patterning lithography](https://mlsanity.com/paper/1402.2459/) (2014)

## Built on by (most cited first, 4 of 4)

- [PatternPaint: Practical Layout Pattern Generation Using Diffusion-Based Inpainting](https://mlsanity.com/paper/2409.01348/) (2024)
- [TorchResist: Open-Source Differentiable Resist Simulator](https://mlsanity.com/paper/2502.06838/) (2025)
- [DiffPattern-Flex: Efficient Layout Pattern Generation via Discrete Diffusion](https://mlsanity.com/paper/2505.04173/) (2025)
- [Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement](https://mlsanity.com/paper/2608.13767/) (2026)

## Abstract (arXiv)

Existing works focus on fixed-size layout pattern generation, while the more practical free-size pattern generation receives limited attention. In this paper, we propose ChatPattern, a novel Large-Language-Model (LLM) powered framework for flexible pattern customization. ChatPattern utilizes a two-part system featuring an expert LLM agent and a highly controllable layout pattern generator. The LLM agent can interpret natural language requirements and operate design tools to meet specified needs, while the generator excels in conditional layout generation, pattern modification, and memory-friendly patterns extension. Experiments on challenging pattern generation setting shows the ability of ChatPattern to synthesize high-quality large-scale patterns.