aDSL: 基于智能体-程序联合设计的三维智能体创作

摘要

程序化表示为三维内容创作提供了一种引人注目的范式，能够实现细粒度编辑、可解释性和显式结构控制。然而，依赖大语言模型（LLM）创作三维程序的智能体工作流仍然脆弱，往往无法将高层意图转化为一致的底层几何结构。我们将这种脆弱性归因于现有程序化接口与LLM推理优势之间的不匹配——后者更偏好语义结构和空间关系，而非脆弱的数值选择。在本文中，我们共同设计了一种以智能体为中心的领域特定语言（aDSL）和一个角色专精的多智能体系统，以弥合这一差距。aDSL通过强调可组合性和空间推理来桥接语义逻辑与几何约束，使智能体能够通过关系运算符而非脆弱的绝对坐标来操作几何。基于aDSL，我们的免训练多智能体系统遵循“计划-执行-评审”循环，对请求进行分解、合成代码，并利用执行反馈迭代修复错误和约束违反。实验表明，这种协同设计提升了鲁棒性、可控性以及对用户意图的忠实性。我们的方法在文生形状和图生形状任务上优于此前基于LLM的基线方法，同时保持了显式结构、可编辑性和可解释性。该方法还支持关节物体创建和结构化场景组合等下游应用。我们的代码可在 https://github.com/sig-pku/aDSL 获取。

English

Programmatic representations provide a compelling paradigm for 3D content creation, enabling fine-grained edits, interpretability, and explicit structural control. Yet, agentic workflows that rely on large language models (LLMs) to author 3D programs remain brittle, often failing to translate high-level intent into consistent low-level geometry. We attribute this fragility to a mismatch between existing programmatic interfaces and the reasoning strengths of LLMs, which favor semantic structure and spatial relations over fragile numeric choices. In this paper, we jointly design an Agent-centric Domain-Specific Language (aDSL) and a role-specialized multi-agent system to close this gap. aDSL bridges semantic logic and geometric constraints by emphasizing composability and spatial reasoning; it enables agents to manipulate geometry through relational operators instead of brittle absolute coordinates. Building on aDSL, our training-free multi-agent system follows a Plan-Execute-Critic loop to decompose requests, synthesize code, and iteratively repair errors and constraint violations using execution feedback. Experiments show that this co-design improves robustness, controllability, and faithfulness to user intent. Our method outperforms prior LLM-based baselines on text-to-shape and image-to-shape tasks while preserving explicit structure, editability, and interpretability. It also enables downstream applications such as articulated object creation and structured scene composition. Our code is available at https://github.com/sig-pku/aDSL.