arXiv cs.AI· Yipeng Gao, Ziyao Zeng, Jinfa Huang, Yijiang Li, Haolin Xiong, Wang Qin, Xinlei Yu, Youheng Yao, Jie Zhang, Kun-Yu Lin, Rong Liu, Yinyuan Zhao, Yajie Zhao, Meiqi Guo, Jiebo Luo, Lei Shu, Yunhao Ge, Xinyu Hu, Laurent Itti·· 2 天前AI 评分37
3DCodeVerse:将 3D 世界作为代码探索
3DCodeVerse: Exploring 3D Worlds as Code
AI 导读
研究者推出 3DCodeVerse 研究生态,让编码智能体大规模生成可编辑、可验证的 3D 内容,包含 3DCodeVerse-2M 大规模可执行 3D 代码数据集、基于多智能体有向无环图的 3DCodeVerse Harness 生成与优化框架,以及系统性 3D 编码实证研究。
正文 · 原文
Authors:Yipeng Gao, Ziyao Zeng, Jinfa Huang, Yijiang Li, Haolin Xiong, Wang Qin, Xinlei Yu, Youheng Yao, Jie Zhang, Kun-Yu Lin, Rong Liu, Yinyuan Zhao, Yajie Zhao, Meiqi Guo, Jiebo Luo, Lei Shu, Yunhao Ge, Xinyu Hu, Laurent Itti
Abstract:We introduce 3DCodeVerse, a research ecosystem that enables coding agents to create editable and verifiable 3D content at scale. 3DCodeVerse comprises large-scale, high-quality datasets of executable 3D code, a coding harness for spatial reasoning and automated verification, and practical guidance for 3D coding. First, we construct 3DCodeVerse-2M, a large-scale curated dataset of standalone 3D executable code. We build this corpus by collecting open-source data, converting specialized representations, and generating new programs with coding agents. Each program is packaged with the source files and associated assets required for execution in its declared environment, along with available descriptions and verification records. Second, we develop the 3DCodeVerse Harness, a multi-agent directed acyclic graph framework for generating and refining 3D content. It uses execution checks, spatial measurements, and visual feedback to automatically evaluate and revise generated programs without human feedback during generation. Third, we conduct systematic empirical studies of 3D coding, establishing baselines with fine-tuned open models and deriving practical guidance through component-level analyses of our harness. Extensive experiments demonstrate that fine-tuning on our dataset significantly improves the 3D coding capabilities of open-source models. Notably, our 3DCodeVerse harness achieves a 90% win rate against Claude Design (3D Object) in pairwise human evaluations, when both are utilized by Claude Opus 5.5.
| Comments: | Project Page: this https URL |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.22341 [cs.CV] |
| (or arXiv:2610.22341v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2610.22341 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Yipeng Gao [view email]
[v1]
Thu, 15 Oct 2026 17:56:07 UTC (6,437 KB)
来源:arXiv cs.AI · arxiv.org