7 citations · 16 across the 34 of their papers we have counts for
7 papers · 1 filter
Identifying Process Improvement Opportunities through Process Execution Benchmarking
Luka Abb, Majid Rafiei, Timotheus Kampik +1
Benchmarking functionalities in current commercial process mining tools allow organizations to contextualize their process performance through high-level performance indicators, su…
Agentic Business Process Management: Practitioner Perspectives on Agent Governance in Business Processes
Hoang Vu, Nataliia Klievtsova, Henrik Leopold +2
With the rise of generative AI, industry interest in software agents is growing. Given the stochastic nature of generative AI-based agents, their effective and safe deployment in o…
Mining Constraints from Reference Process Models for Detecting Best-Practice Violations in Event Logs
Adrian Rebmann, Timotheus Kampik, Carl Corea +1
Detecting undesired process behavior is one of the main tasks of process mining and various conformance-checking techniques have been developed to this end. These techniques typica…
Leveraging Generative AI for Extracting Process Models from Multimodal Documents
Marvin Voelter, Raheleh Hadian, Timotheus Kampik +2
This paper presents an investigation of the capabilities of Generative Pre-trained Transformers (GPTs) to auto-generate graphical process models from multi-modal (i.e., text- and i…
Large Process Models: A Vision for Business Process Management in the Age of Generative AI
Timotheus Kampik, Christian Warmuth, Adrian Rebmann +12
The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over…
Reinforcement Learning-supported AB Testing of Business Process Improvements: An Industry Perspective
Aaron Friedrich Kurz, Timotheus Kampik, Luise Pufahl +1
In order to better facilitate the need for continuous business process improvement, the application of DevOps principles has been proposed. In particular, the AB-BPM methodology ap…