3 papers
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…
math.OC2026
Structure-Aware Optimization of Decision Diagrams for Health Guidance via Integer Programming
Nanako Shimaoka, Naoyuki Kamiyama, Shinji Hotta +5
In this paper, we consider a structure-aware optimization problem for decision diagrams used for health guidance. In particular, we focus on decision diagrams that decide to whom p…