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LLM4PM: A case study on using Large Language Models for Process Modeling in Enterprise Organizations

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arxiv 2407.17478 v1 pith:XTC2CAZX submitted 2024-07-01 cs.HC cs.AIcs.CLcs.CYcs.LG

classification cs.HCcs.AIcs.CLcs.CYcs.LG
keywords processprodigycasefirsthiltilanguagelargemodellers
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We investigate the potential of using Large Language Models (LLM) to support process model creation in organizational contexts. Specifically, we carry out a case study wherein we develop and test an LLM-based chatbot, PRODIGY (PROcess moDellIng Guidance for You), in a multinational company, the Hilti Group. We are particularly interested in understanding how LLM can aid (human) modellers in creating process flow diagrams. To this purpose, we first conduct a preliminary user study (n=10) with professional process modellers from Hilti, inquiring for various pain-points they encounter in their daily routines. Then, we use their responses to design and implement PRODIGY. Finally, we evaluate PRODIGY by letting our user study's participants use PRODIGY, and then ask for their opinion on the pros and cons of PRODIGY. We coalesce our results in actionable takeaways. Through our research, we showcase the first practical application of LLM for process modelling in the real world, shedding light on how industries can leverage LLM to enhance their Business Process Management activities.

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  1. Evaluating Large Language Models on Business Process Modeling: Framework, Benchmark, and Self-Improvement Analysis

    cs.DB 2024-11 conditional novelty 5.0 of 10

    A benchmark of 20 business processes and 16 large language models finds Claude-3.5-Sonnet produces the highest-quality process models, and suggests that output optimization improves weaker models.

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