8 papers
Organizational Memory for Agentic Business Process Execution
Lukas Kirchdorfer, Adrian Rebmann, Christian Warmuth +3
LLM-based agents offer new opportunities for automating business process execution beyond the limits of rule-based systems. However, general-purpose LLMs lack the organization-spec…
Agent Behavior Mining: Generative AI Agent Governance in Business Processes
Hoang Vu, Maximilian Körner, Adrian Rebmann +4
As organizations increasingly deploy generative AI agents to automate business processes, they face a governance dilemma: although these agents can increase operational flexibility…
Bridging Imperative Process Models and Process Data Queries-Translation and Relaxation
Abdur Rehman Anwar Qureshi, Adrian Rebmann, Timotheus Kampik +2
Business process management is increasingly practiced using data-driven approaches. Still, classical imperative process models, which are typically formalized using Petri nets, are…
LLMs that Understand Processes: Instruction-tuning for Semantics-Aware Process Mining
Vira Pyrih, Adrian Rebmann, Han van der Aa
Process mining is increasingly using textual information associated with events to tackle tasks such as anomaly detection and process discovery. Such semantics-aware process mining…
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…
Detecting Undesired Process Behavior by Means of Retrieval Augmented Generation
Michael Grohs, Adrian Rebmann, Jana-Rebecca Rehse
Conformance checking techniques detect undesired process behavior by comparing process executions that are recorded in event logs to desired behavior that is captured in a dedicate…