3 papers
cs.CL2026
Improving LLM-Generated Process Model Quality Through Reinforcement Learning: The Role of Reward Function Design
Alexander Rombach, Chantale Lauer, Nijat Mehdiyev
Large language models (LLMs) can generate BPMN process models from natural-language descriptions, yet supervised fine-tuning (SFT) limits their output quality to the patterns prese…
cs.AI2026
Neuro-Symbolic Agents for Regulated Process Automation: Challenges and Research Agenda
Alexander Rombach, Chantale Lauer, Nijat Mehdiyev
LLM-based agents are entering regulated industries where they automate judgment intensive quality management processes. We argue that symbolic structures already embedded in these…
cs.HC2026
Human-Centered Evaluation of an LLM-Based Process Modeling Copilot: A Mixed-Methods Study with Domain Experts
Chantale Lauer, Peter Pfeiffer, Nijat Mehdiyev
Integrating Large Language Models (LLMs) into business process management tools promises to democratize Business Process Model and Notation (BPMN) modeling for non-experts. While a…