3 papers
cs.SE2026
Automated BPMN Model Generation from Textual Process Descriptions: A Multi-Stage LLM-Driven Approach
Ion Matei, Maksym Zhenirovskyy, Praveen Kumar Menaka Sekar +1
Automatically reconstructing BPMN models from unstructured natural-language descriptions remains challenging due to heterogeneous modeling conventions, multilingual sources, and th…
cs.SE2026
Ambiguity Detection and Elimination in Automated Executable Process Modeling
Ion Matei, Praveen Kumar Menaka Sekar, Maksym Zhenirovskyy +4
Automated generation of executable Business Process Model and Notation (BPMN) models from natural-language specifications is increasingly enabled by large language models. However,…
cs.AI2026
Automatic Generation of Executable BPMN Models from Medical Guidelines
Praveen Kumar Menaka Sekar, Ion Matei, Maksym Zhenirovskyy +4
We present an end-to-end pipeline that converts healthcare policy documents into executable, data-aware Business Process Model and Notation (BPMN) models using large language model…