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Bridging Model-Driven Engineering and Machine Learning for Adaptive User Interface Generation: A Compact Metamodel, a Learned Layout Selector, and a Reproducible Multi-Metric Evaluation

2026-06-22

Abstract excerpt

Automatic user-interface (UI) generation is pursued by two communities that rarely meet. Model-driven engineering (MDE) offers rigour, traceability, and reproducibility but is held back by the cognitive cost of elaborate modelling languages; machine learning (ML) offers flexibility and strong results on visual-to-code tasks but produces opaque, hard-to-reproduce systems that falter on structurally irregular inputs...

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Literature Corpus work: 2b6abaf4-91cb-523d-9a45-9be75d784aaa
DOI: 10.20944/preprints202606.1517.v1

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