Process Modeling with Large Language Models

Author:

Kourani HumamORCID,Berti AlessandroORCID,Schuster DanielORCID,van der Aalst Wil M. P.ORCID

Publisher

Springer Nature Switzerland

Reference30 articles.

1. Bellan, P., Dragoni, M., Ghidini, C.: A qualitative analysis of the state of the art in process extraction from text. In: Vizzari, G., Palmonari, M., Orlandini, A. (eds.) Proceedings of the AIxIA 2020 Discussion Papers Workshop co-located with the the 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA2020), Anywhere, November 27th, 2020, CEUR Workshop Proceedings, vol. 2776, pp. 19–30. CEUR-WS.org (2020)

2. Bellan, P., van der Aa, H., Dragoni, M., Ghidini, C., Ponzetto, S.P.: PET: an annotated dataset for process extraction from natural language text tasks. In: Cabanillas, C., Garmann-Johnsen, N.F., Koschmider, A. (eds.) Business Process Management Workshops - BPM 2022. LNBIP, vol. 460, pp. 315–321. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-25383-6_23

3. Berti, A., Schuster, D., van der Aalst, W.M.P.: Abstractions, scenarios, and prompt definitions for process mining with LLMs: a case study. In: De Weerdt, J., Pufahl, L. (eds.) Business Process Management Workshops - BPM 2023. LNBIP, vol. 492, pp. 427–439. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-50974-2_32

4. Busch, K., Rochlitzer, A., Sola, D., Leopold, H.: Just tell me: prompt engineering in business process management. In: van der Aa, H., Bork, D., Proper, H.A., Schmidt, R. (eds.) Enterprise, Business-Process and Information Systems Modeling, BPMDS 2023, EMMSAD 2023. LNBIP, vol. 479, pp. 3–11. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-34241-7_1

5. Chen, S., Liao, H.: Bert-log: anomaly detection for system logs based on pre-trained language model. Appl. Artif. Intell. 36(1) (2022)

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