arXiv cs.AI· R. Kenny Jones, Jiajun Wu, Maneesh Agrawala·· 3 天前AI 评分26
Co-DSL：人机协同设计可复用空间概念用于布局生成
Co-DSL: Human-LLM Co-design of Reusable Spatial Concepts for Layout Generation
AI 导读
Co-DSL 让用户与 LLM 协同设计可复用的空间概念库，用户提供描述后由 LLM 转为初始实现，再通过示例场景观察执行行为并给出轻量反馈，由 LLM 修正概念逻辑。
正文 · 原文
Abstract:We present Co-DSL, a framework in which users and LLMs co-design reusable spatial concepts for layout generation. In the first stage, our system allows users to create a library of personalized operations. To add a concept, a user provides a description, which the LLM converts into an initial implementation. The user can then observe the concept's execution behavior over example scenarios and provide lightweight feedback to the LLM, which revises the concept's implementation logic. In the second stage, given a library, an LLM can author a layout program that meets a new layout request from a user. Executing a layout program instantiates a concept-graph, a declarative composition of library concepts. In this way, we require the LLM only to specify which concepts should hold, while we use a solver to search for a layout that satisfies them. Across five spatial layout domains, we find that Co-DSL libraries let LLMs capture layout patterns that are challenging for prior fixed-operation systems, and demonstrate that our concept-graph representation is needed for LLMs to reliably compose concepts together. We further find that Co-DSL lets LLMs author generative layout programs that expose high-level parametric controls users can manipulate to explore a distribution of related layouts without re-prompting.
| Comments: | Project page: this http URL |
| Subjects: | Graphics (cs.GR); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2610.15290 [cs.GR] |
| (or arXiv:2610.15290v1 [cs.GR] for this version) | |
| https://doi.org/10.48550/arXiv.2610.15290 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: R. Kenny Jones [view email]
[v1]
Sun, 11 Oct 2026 02:49:48 UTC (22,797 KB)
来源：arXiv cs.AI · arxiv.org