| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | PROMISE : a framework for model-driven stateful prompt orchestration |
| Autor/-in: | Wu, Wenyuan Heierli, Jasmin Meisterhans, Max Moser, Adrian Färber, Andri Dolata, Mateusz Gavagnin, Elena de Spindler, Alexandre Schwabe, Gerhard |
| et. al: | No |
| DOI: | 10.1007/978-3-031-61000-4_18 |
| Tagungsband: | Intelligent Information Systems |
| Herausgeber/-in des übergeordneten Werkes: | Islam, Shareeful Sturm, Arnon |
| Seite(n): | 157 |
| Seiten bis: | 165 |
| Angaben zur Konferenz: | 36th International Conference on Advanced Information Systems Engineering (CAiSE), Limassol, Cyprus, 3-7 June 2024 |
| Erscheinungsdatum: | 29-Mai-2024 |
| Verlag / Hrsg. Institution: | Springer |
| Verlag / Hrsg. Institution: | Cham |
| ISBN: | 978-3-031-60999-2 978-3-031-61000-4 |
| Sprache: | Englisch |
| Schlagwörter: | Framework; Prompt orchestration; Language model |
| Fachgebiet (DDC): | 006: Spezielle Computerverfahren 410.285: Computerlinguistik |
| Zusammenfassung: | The advent of increasingly powerful language models has raised expectations for conversational interactions. However, controlling these models is a challenge, emphasizing the need to be able to investigate the feasibility and value of their application. We present PROMISE (Available at: https://github.com/zhaw-iwi/promise), a framework that facilitates the development of complex conversational interactions with information systems. Its use of state machine modeling concepts enables model-driven, dynamic prompt orchestration across hierarchically nested states and transitions. This improves the control of language models’ behavior and thus enables their effective and efficient use. We show the applications of PROMISE in health information systems and demonstrate its ability to handle complex interactions. |
| URI: | https://www.zora.uzh.ch/id/eprint/259993/ https://digitalcollection.zhaw.ch/handle/11475/31093 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Management and Law |
| Organisationseinheit: | Institut für Wirtschaftsinformatik (IWI) |
| Enthalten in den Sammlungen: | Publikationen School of Management and Law |
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Wu, W., Heierli, J., Meisterhans, M., Moser, A., Färber, A., Dolata, M., Gavagnin, E., de Spindler, A., & Schwabe, G. (2024). PROMISE : a framework for model-driven stateful prompt orchestration [Conference paper]. In S. Islam & A. Sturm (Eds.), Intelligent Information Systems (pp. 157–165). Springer. https://doi.org/10.1007/978-3-031-61000-4_18
Wu, W. et al. (2024) ‘PROMISE : a framework for model-driven stateful prompt orchestration’, in S. Islam and A. Sturm (eds) Intelligent Information Systems. Cham: Springer, pp. 157–165. Available at: https://doi.org/10.1007/978-3-031-61000-4_18.
W. Wu et al., “PROMISE : a framework for model-driven stateful prompt orchestration,” in Intelligent Information Systems, May 2024, pp. 157–165. doi: 10.1007/978-3-031-61000-4_18.
WU, Wenyuan, Jasmin HEIERLI, Max MEISTERHANS, Adrian MOSER, Andri FÄRBER, Mateusz DOLATA, Elena GAVAGNIN, Alexandre DE SPINDLER und Gerhard SCHWABE, 2024. PROMISE : a framework for model-driven stateful prompt orchestration. In: Shareeful ISLAM und Arnon STURM (Hrsg.), Intelligent Information Systems [online]. Conference paper. Cham: Springer. 29 Mai 2024. S. 157–165. ISBN 978-3-031-60999-2. Verfügbar unter: https://www.zora.uzh.ch/id/eprint/259993/
Wu, Wenyuan, Jasmin Heierli, Max Meisterhans, Adrian Moser, Andri Färber, Mateusz Dolata, Elena Gavagnin, Alexandre de Spindler, and Gerhard Schwabe. 2024. “PROMISE : A Framework for Model-Driven Stateful Prompt Orchestration.” Conference paper. In Intelligent Information Systems, edited by Shareeful Islam and Arnon Sturm, 157–65. Cham: Springer. https://doi.org/10.1007/978-3-031-61000-4_18.
Wu, Wenyuan, et al. “PROMISE : A Framework for Model-Driven Stateful Prompt Orchestration.” Intelligent Information Systems, edited by Shareeful Islam and Arnon Sturm, Springer, 2024, pp. 157–65, https://doi.org/10.1007/978-3-031-61000-4_18.
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