Record link: 
http://hdl.handle.net/20.500.12708/205512
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Title: 
How Does UML Look and Sound? Using AI to Interpret UML Diagrams Through Multimodal Evidence
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Citation: 
Gavric, A., Bork, D., & Proper, H. A. (2024). How Does UML Look and Sound? Using AI to Interpret UML Diagrams Through Multimodal Evidence. In Advances in Conceptual Modeling (pp. 187–197). https://doi.org/10.1007/978-3-031-75599-6_14
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Publisher DOI: 
10.1007/978-3-031-75599-6_14
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Gavric, Aleksandar 
Bork, Dominik 
Proper, Henderik A. 
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Organisational Unit: 
E194-03 - Forschungsbereich Business Informatics 
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Published in: 
Advances in Conceptual Modeling 
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ISBN: 
978-3-031-75599-6
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Volume: 
14932
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Date (published): 
2024
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Event name: 
7th International Workshop on Empirical Methods in Conceptual Modeling (EmpER 2024) co-located to 43rd International Conference on Conceptual Modeling (ER 2024) 
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Event date: 
28-Oct-2024 - 31-Oct-2024
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Event place: 
Pittsburgh, United States of America (the)
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Number of Pages: 
11
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Peer reviewed: 
Yes
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Keywords: 
multi-modal AI; Conceptual Modeling; Comprehension; Large Language Models (LLMs)
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 90%
5020 - Wirtschaftswissenschaften: 10%
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Appears in Collections:
Conference Paper

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