aDSL: Agentic 3D Creation via Joint Agent-Program Design

2026-08-18

AI Summary

为解决3D内容创作中大语言模型生成程序的脆弱性问题，提出了一种基于Agent的领域特定语言aDSL及多代理系统，通过强调组合性和空间推理来提高鲁棒性和用户意图的忠实度。

Abstract

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.

Problem

• Agentic 3D Creation
• Large Language Models
• Programmatic Representations
• Semantic Structure
• Spatial Relations

Innovation

• Agent-centric Domain-Specific Language
• spatial reasoning
• Plan-Execute-Critic loop
• multi-agent system