Record link: 
http://hdl.handle.net/20.500.12708/230894
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Title: 
Amalgam: Hybrid LLM-PGM Synthesis Algorithm for Accuracy and Realism
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Citation: 
Kapenekakis, A., Thomsen, B., Hose, K., & Albano, M. (2026). Amalgam: Hybrid LLM-PGM Synthesis Algorithm for Accuracy and Realism. arXiv. https://doi.org/10.48550/ARXIV.2603.27254
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Publisher DOI: 
10.48550/ARXIV.2603.27254
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Publication Type: 
Preprint
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Language: 
English
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Authors: 
Kapenekakis, Antheas 
Thomsen, Bent 
Hose, Katja 
Albano, Michele 
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Organisational Unit: 
E194-07 - Forschungsbereich Data Management 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
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Date (published): 
28-Mar-2026
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Number of Pages: 
11
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Preprint Server: 
arXiv 
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Keywords: 
LLMs; Data Synthesis; Probabilistic Graph Models
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Research Areas: 
Logic and Computation: 20%
Information Systems Engineering: 80%
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Science Branch: 
1020 - Informatik: 90%
1010 - Mathematik: 10%
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Appears in Collections:
Preprint

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