From Image to UML: First Results of Image Based UML Diagram Generation Using LLMs
Not on the map. Why?
Abstract (arXiv)
In software engineering processes, systems are first specified using a modeling language such as UML. These initial designs are often collaboratively created, many times in meetings where different domain experts use whiteboards, paper or other types of quick supports to create drawings and blueprints that then will need to be formalized. These proper, machine-readable, models are key to ensure models can be part of automated processes (e.g. input of a low-code generation pipeline, a model-based testing system, ...). But going from hand-drawn diagrams to actual models is a time-consuming process that sometimes ends up with such drawings just added as informal images to the software documentation, reducing their value a lot. To avoid this tedious task, we explore the usage of Large Language Models (LLM) to generate the formal representation of (UML) models from a given drawing. More specifically, we have evaluated the capabilities of different LLMs to convert images of UML class diagrams into the actual models represented in the images. While the results are good enough to use such an approach as part of a model-driven engineering pipeline we also highlight some of their current limitations and the need to keep the human in the loop to overcome those limitations.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Apr 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 5; 2026: 5.
11 papers.
- 2025Generative AI and Empirical Software Engineering: A Paradigm Shiftcited by 9
- 2025Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language Modelscited by 7
- 2025Multi-modal Summarization in Model-Based Engineering: Automotive Software Development Case Studycited by 6
- 2025Assessing LLMs for Front-end Software Architecture Knowledgecited by 2
- 2024The importance of visual modelling languages in generative software engineeringcited by 1
- 2025Measuring Visual Understanding in Telecom domain: Performance Metrics for Image-to-UML conversion using VLMscited by 1
- 2026Code2UML: Agentic LLMs with context engineering for scalable software visualizationcited by 1
- 2026LLM-based Automated Architecture View Generation: Where Are We Now?cited by 0
- 2026Unlocking UML Class Diagram Understanding in Vision Language Modelscited by 0
- 2026Prior Bias in Vision Language Models on UML Diagram Interpretationcited by 0
- 2026CAS2UML: A Handwritten Sketch-to-PlantUML Dataset for Class and Activity Diagramscited by 0
- 2026CAS2UML: A Handwritten Sketch-to-PlantUML Dataset for Class and Activity Diagrams7 Aug 2026
- 2026Prior Bias in Vision Language Models on UML Diagram Interpretation3 Jul 2026
- 2026Code2UML: Agentic LLMs with context engineering for scalable software visualization23 May 2026
- 2026Unlocking UML Class Diagram Understanding in Vision Language Models12 May 2026
- 2026LLM-based Automated Architecture View Generation: Where Are We Now?22 Mar 2026
- 2025Measuring Visual Understanding in Telecom domain: Performance Metrics for Image-to-UML conversion using VLMs15 Sep 2025
- 2025Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language Models15 Mar 2025
- 2025Multi-modal Summarization in Model-Based Engineering: Automotive Software Development Case Study6 Mar 2025
- 2025Assessing LLMs for Front-end Software Architecture Knowledge26 Feb 2025
- 2025Generative AI and Empirical Software Engineering: A Paradigm Shift12 Feb 2025
- 2024The importance of visual modelling languages in generative software engineering27 Nov 2024