用带求解器的分层语言让大模型轻松生成复杂三维设计。
A Solver-Aided Hierarchical Language for LLM-Driven CAD Design
- 设计分层领域语言AIDL，将空间推理交给几何约束求解器。
- 少样本下生成效果优于有训练数据的OpenSCAD，更接近提示意图。
- 适合需要精准几何生成的工业设计与自动化建模场景。
大语言模型在处理各类结构化和非结构化生成任务上表现卓越，但在计算机辅助设计（CAD）中生成过程式几何时仍面临挑战，主要源于缺乏空间推理能力以及需进行长程复杂规划。本文提出一种带求解器的分层领域语言AIDL，将空间推理任务交由几何约束求解器完成。在少样本条件下，AIDL生成的视觉结果更贴近用户提示，且生成的模型更易后续处理与理解，性能超越使用训练数据的OpenSCAD语言。
原文摘要 · Abstract (English)
Large language models (LLMs) have been enormously successful in solving a wide variety of structured and unstructured generative tasks, but they struggle to generate procedural geometry in Computer Aided Design (CAD). These difficulties arise from an inability to do spatial reasoning and the necessity to guide a model through complex, long range planning to generate complex geometry. We enable generative CAD Design with LLMs through the introduction of a solver-aided, hierarchical domain specific language (DSL) called AIDL, which offloads the spatial reasoning requirements to a geometric constraint solver. Additionally, we show that in the few-shot regime, AIDL outperforms even a language with in-training data (OpenSCAD), both in terms of generating visual results closer to the prompt and creating objects that are easier to post-process and reason about.
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