Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation

Fuente: arXiv
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Main Authors: Gumin, Maxim, Han, Do Heon, Yoo, Seung Jean, Ganeshan, Aditya, Jones, R. Kenny, Aguina-Kang, Rio, Morris, Stewart, Ritchie, Daniel
Format: Preprint
Published: 2025
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author Gumin, Maxim
Han, Do Heon
Yoo, Seung Jean
Ganeshan, Aditya
Jones, R. Kenny
Aguina-Kang, Rio
Morris, Stewart
Ritchie, Daniel
author_facet Gumin, Maxim
Han, Do Heon
Yoo, Seung Jean
Ganeshan, Aditya
Jones, R. Kenny
Aguina-Kang, Rio
Morris, Stewart
Ritchie, Daniel
contents Current methods for generating 3D scene layouts from text predominantly follow a declarative paradigm, where a Large Language Model (LLM) specifies high-level constraints that are then resolved by a separate solver. This paper challenges that consensus by introducing a more direct, imperative approach. We task an LLM with generating a step-by-step program that iteratively places each object relative to those already in the scene. This paradigm simplifies the underlying scene specification language, enabling the creation of more complex, varied, and highly structured layouts that are difficult to express declaratively. To improve the robustness, we complement our method with a novel, LLM-free error correction mechanism that operates directly on the generated code, iteratively adjusting parameters within the program to resolve collisions and other inconsistencies. In forced-choice perceptual studies, human participants overwhelmingly preferred our imperative layouts, choosing them over those from two state-of-the-art declarative systems 82% and 94% of the time, demonstrating the significant potential of this alternative paradigm. Finally, we present a simple automated evaluation metric for 3D scene layout generation that correlates strongly with human judgment.
format Preprint
id arxiv_https___arxiv_org_abs_2504_05482
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation
Gumin, Maxim
Han, Do Heon
Yoo, Seung Jean
Ganeshan, Aditya
Jones, R. Kenny
Aguina-Kang, Rio
Morris, Stewart
Ritchie, Daniel
Graphics
Programming Languages
Current methods for generating 3D scene layouts from text predominantly follow a declarative paradigm, where a Large Language Model (LLM) specifies high-level constraints that are then resolved by a separate solver. This paper challenges that consensus by introducing a more direct, imperative approach. We task an LLM with generating a step-by-step program that iteratively places each object relative to those already in the scene. This paradigm simplifies the underlying scene specification language, enabling the creation of more complex, varied, and highly structured layouts that are difficult to express declaratively. To improve the robustness, we complement our method with a novel, LLM-free error correction mechanism that operates directly on the generated code, iteratively adjusting parameters within the program to resolve collisions and other inconsistencies. In forced-choice perceptual studies, human participants overwhelmingly preferred our imperative layouts, choosing them over those from two state-of-the-art declarative systems 82% and 94% of the time, demonstrating the significant potential of this alternative paradigm. Finally, we present a simple automated evaluation metric for 3D scene layout generation that correlates strongly with human judgment.
title Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation
topic Graphics
Programming Languages
url https://arxiv.org/abs/2504.05482