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cs.AI2024
Towards a Benchmark for Large Language Models for Business Process Management Tasks
Kiran Busch, Henrik Leopold
An increasing number of organizations are deploying Large Language Models (LLMs) for a wide range of tasks. Despite their general utility, LLMs are prone to errors, ranging from in…
cs.AI2024
xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence Models
Kiran Busch, Timotheus Kampik, Henrik Leopold
The identification of undesirable behavior in event logs is an important aspect of process mining that is often addressed by anomaly detection methods. Traditional anomaly detectio…