Enabling the Discovery of Manual Processes Using a Multi-modal Activity Recognition Approach. - Adrian Rebmann; Andreas Emrich; Peter Fettke (Business Process Management Workshops, 2019)

Improving Business Model Configuration through a Question-based Approach. - Sarah Rübel; Adrian Rebmann; Andreas Emrich; Sabine Klein; Peter Loos (Wirtschaftsinformatik, 2019)

IoT-Based Activity Recognition for Process Assistance in Human-Robot Disaster Response. - Adrian Rebmann; Jana-Rebecca Rehse; Mira Pinter; Marius Schnaubelt; Kevin Daun; Peter Fettke (BPM (Forum), 2020)

Hands-on Process Discovery with Python - Utilizing Jupyter Notebook for the Digital Assistance in Higher Education. - Adrian Rebmann; Alexander Beuther; Steffen Schumann; Peter Fettke (Modellierung (Companion), 2020)

Abstracting Low-level Event Data for Meaningful Process Analysis. - Adrian Rebmann (BPM (PhD/Demos), 2021)

Extracting Semantic Process Information from the Natural Language in Event Logs. - Adrian Rebmann; Han van der Aa (CAiSE, 2021)

Natural language-based detection of semantic execution anomalies in event logs. - Han van der Aa; Adrian Rebmann; Henrik Leopold (Inf. Syst., 2021)

Uncovering Object-Centric Data in Classical Event Logs for the Automated Transformation from XES to OCEL. - Adrian Rebmann; Jana-Rebecca Rehse; Han van der Aa (BPM, 2022)

GECCO: Constraint-driven Abstraction of Low-level Event Logs. - Adrian Rebmann; Matthias Weidlich 001; Han van der Aa (ICDE, 2022)

Multi-perspective Identification of Event Groups for Event Abstraction. - Adrian Rebmann; Peter Pfeiffer; Peter Fettke; Han van der Aa (ICPM Workshops, 2022)

Enabling semantics-aware process mining through the automatic annotation of event logs. - Adrian Rebmann; Han van der Aa (Inf. Syst., 2022)

BPMN2Constraints: Breaking Down BPMN Diagrams into Declarative Process Query Constraints. - Arvid Bergmann; Adrian Rebmann; Timotheus Kampik (BPM (Demos / Resources Forum), 2023)

Does This Make Sense? Machine Learning-Based Detection of Semantic Anomalies in Business Processes. - Julian Caspary; Adrian Rebmann; Han van der Aa (BPM, 2023)

Unsupervised Task Recognition from User Interaction Streams. - Adrian Rebmann; Han van der Aa (CAiSE, 2023)

M-viz: A Tool for the Step-by-step Visualization of the Inductive Miner. - Florian Lang 004; Din Hida; Yingjie Bian; Adrian Rebmann; Han van der Aa (ICPM Doctoral Consortium / Demo, 2023)

From OCEL to DOCEL - Datasets and Automated Transformation. - Alexandre Goossens; Adrian Rebmann; Johannes De Smedt; Jan Vanthienen; Han van der Aa (ICPM Workshops, 2023)

Large Process Models: Business Process Management in the Age of Generative AI. - Timotheus Kampik; Christian Warmuth; Adrian Rebmann; Ron Agam; Lukas N. P. Egger; Andreas Gerber; Johannes Hoffart; Jonas Kolk; Philipp Herzig; Gero Decker; Han van der Aa; Artem Polyvyanyy; et al. (CoRR, 2023)

Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks. - Adrian Rebmann; Fabian David Schmidt; Goran Glavas; Han van der Aa (ICPM, 2024)

Mining Constraints from Reference Process Models for Detecting Best-Practice Violations in Event Log. - Adrian Rebmann; Timotheus Kampik; Carl Corea; Han van der Aa (CoRR, 2024)

Recognizing task-level events from user interaction data. - Adrian Rebmann; Han van der Aa (Inf. Syst., 2024)

Towards Automating the Severity Assessment of Conformance Deviations. - Michael Grohs; Adrian Rebmann (EMISA, 2025)

On the Potential of Large Language Models to Solve Semantics-Aware Process Mining Tasks. - Adrian Rebmann; Fabian David Schmidt; Goran Glavas; Han van der Aa (CoRR, 2025)

Detecting Undesired Process Behavior by Means of Retrieval Augmented Generation. - Michael Grohs; Adrian Rebmann; Jana-Rebecca Rehse (CoRR, 2025)