ChatPattern: Layout Pattern Customization via Natural Language
This addresses a practical need in design automation for flexible pattern generation, though it appears incremental as it builds on existing layout generation methods with LLM integration.
The paper tackles the problem of free-size layout pattern generation, which has received limited attention compared to fixed-size generation, by proposing ChatPattern, an LLM-powered framework that synthesizes high-quality large-scale patterns through natural language customization.
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.