A hierarchical partial-order algorithm derives concurrent traces from event logs and aggregates them into sound-by-construction, perfectly fitting process models while abstracting choices and loops for compactness.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2025 2verdicts
UNVERDICTED 2representative citing papers
LLMs override explicit source evidence with internal knowledge when modeling business processes, creating a measurable reliability risk in analytical tasks.
citing papers explorer
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Revealing Inherent Concurrency in Event Data: A Partial Order Approach to Process Discovery
A hierarchical partial-order algorithm derives concurrent traces from event logs and aggregates them into sound-by-construction, perfectly fitting process models while abstracting choices and loops for compactness.
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Knowledge-Driven Hallucination in Large Language Models: An Empirical Study on Process Modeling
LLMs override explicit source evidence with internal knowledge when modeling business processes, creating a measurable reliability risk in analytical tasks.