Summary of Scenegenagent: Precise Industrial Scene Generation with Coding Agent, by Xiao Xia et al.
SceneGenAgent: Precise Industrial Scene Generation with Coding Agent
by Xiao Xia, Dan Zhang, Zibo Liao, Zhenyu Hou, Tianrui Sun, Jing Li, Ling Fu, Yuxiao Dong
First submitted to arxiv on: 29 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG); Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces SceneGenAgent, a Large Language Model (LLM) based agent for generating industrial scenes through C# code. This challenge requires precise measurements and positioning, necessitating complex planning over spatial arrangement. SceneGenAgent ensures precise layout planning through structured format, verification, and iterative refinement to meet quantitative requirements. The results show that LLMs powered by SceneGenAgent exceed their original performance, reaching up to 81.0% success rate in real-world industrial scene generation tasks. Additionally, the paper constructs SceneInstruct, a dataset designed for fine-tuning open-source LLMs to integrate into SceneGenAgent. Fine-tuning yields significant performance improvements, with Llama3.1-70B approaching the capabilities of GPT-4o. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about creating virtual scenes that are used in industrial manufacturing simulations. It’s hard for computers to make these scenes because they require precise measurements and positioning. The authors created a special program called SceneGenAgent that helps computers generate industrial scenes. This program makes sure the layout of the scene is correct and can even fix mistakes if needed. The results show that this program works well, with a success rate of 81%. The paper also creates a dataset to help other programs learn how to make these scenes. |
Keywords
» Artificial intelligence » Fine tuning » Gpt » Large language model
