Process Model

Process models represent structured workflows, aiming to describe, analyze, and optimize real-world processes across diverse domains. Current research emphasizes automated process model generation from textual descriptions or event logs, utilizing techniques like large language models (LLMs), neural networks, and process mining algorithms (e.g., Petri nets, process trees). This work is driven by the need for efficient process discovery and analysis, particularly in complex systems where manual modeling is impractical, with applications ranging from business process management to healthcare and manufacturing. Improved model interpretability and robustness against adversarial attacks are also significant research foci.