---
_id: '58724'
author:
- first_name: Katharina
full_name: Brennig, Katharina
last_name: Brennig
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
last_name: Müller
citation:
ama: 'Brennig K, Kaltenpoth SB, Müller O. Straight Outta Logs: Can Large Language
Models Overcome Preprocessing in Next Event Prediction? In: Lecture Notes in
Business Information Processing. Springer Nature Switzerland; 2025. doi:10.1007/978-3-031-78666-2_15'
apa: 'Brennig, K., Kaltenpoth, S. B., & Müller, O. (2025). Straight Outta Logs:
Can Large Language Models Overcome Preprocessing in Next Event Prediction? In
Lecture Notes in Business Information Processing. Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-78666-2_15'
bibtex: '@inbook{Brennig_Kaltenpoth_Müller_2025, place={Cham}, title={Straight Outta
Logs: Can Large Language Models Overcome Preprocessing in Next Event Prediction?},
DOI={10.1007/978-3-031-78666-2_15},
booktitle={Lecture Notes in Business Information Processing}, publisher={Springer
Nature Switzerland}, author={Brennig, Katharina and Kaltenpoth, Sascha Benjamin
and Müller, Oliver}, year={2025} }'
chicago: 'Brennig, Katharina, Sascha Benjamin Kaltenpoth, and Oliver Müller. “Straight
Outta Logs: Can Large Language Models Overcome Preprocessing in Next Event Prediction?”
In Lecture Notes in Business Information Processing. Cham: Springer Nature
Switzerland, 2025. https://doi.org/10.1007/978-3-031-78666-2_15.'
ieee: 'K. Brennig, S. B. Kaltenpoth, and O. Müller, “Straight Outta Logs: Can Large
Language Models Overcome Preprocessing in Next Event Prediction?,” in Lecture
Notes in Business Information Processing, Cham: Springer Nature Switzerland,
2025.'
mla: 'Brennig, Katharina, et al. “Straight Outta Logs: Can Large Language Models
Overcome Preprocessing in Next Event Prediction?” Lecture Notes in Business
Information Processing, Springer Nature Switzerland, 2025, doi:10.1007/978-3-031-78666-2_15.'
short: 'K. Brennig, S.B. Kaltenpoth, O. Müller, in: Lecture Notes in Business Information
Processing, Springer Nature Switzerland, Cham, 2025.'
date_created: 2025-02-20T09:11:59Z
date_updated: 2025-05-07T14:19:42Z
department:
- _id: '196'
doi: 10.1007/978-3-031-78666-2_15
language:
- iso: eng
place: Cham
publication: Lecture Notes in Business Information Processing
publication_identifier:
isbn:
- '9783031786655'
- '9783031786662'
issn:
- 1865-1348
- 1865-1356
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: 'Straight Outta Logs: Can Large Language Models Overcome Preprocessing in Next
Event Prediction?'
type: book_chapter
user_id: '50640'
year: '2025'
...
---
_id: '64870'
author:
- first_name: Marcel
full_name: Meyer, Marcel
id: '105120'
last_name: Meyer
orcid: ' 0009-0005-9136-8525'
- first_name: David Ricardo
full_name: Zapata Gonzalez, David Ricardo
id: '105506'
last_name: Zapata Gonzalez
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: Meyer M, Zapata Gonzalez DR, Kaltenpoth SB, Müller O. Benchmarking Time Series
Foundation Models for Short-Term Household Electricity Load Forecasting. IEEE
Access. 2025;13:218141-218153. doi:10.1109/access.2025.3648056
apa: Meyer, M., Zapata Gonzalez, D. R., Kaltenpoth, S. B., & Müller, O. (2025).
Benchmarking Time Series Foundation Models for Short-Term Household Electricity
Load Forecasting. IEEE Access, 13, 218141–218153. https://doi.org/10.1109/access.2025.3648056
bibtex: '@article{Meyer_Zapata Gonzalez_Kaltenpoth_Müller_2025, title={Benchmarking
Time Series Foundation Models for Short-Term Household Electricity Load Forecasting},
volume={13}, DOI={10.1109/access.2025.3648056},
journal={IEEE Access}, publisher={Institute of Electrical and Electronics Engineers
(IEEE)}, author={Meyer, Marcel and Zapata Gonzalez, David Ricardo and Kaltenpoth,
Sascha Benjamin and Müller, Oliver}, year={2025}, pages={218141–218153} }'
chicago: 'Meyer, Marcel, David Ricardo Zapata Gonzalez, Sascha Benjamin Kaltenpoth,
and Oliver Müller. “Benchmarking Time Series Foundation Models for Short-Term
Household Electricity Load Forecasting.” IEEE Access 13 (2025): 218141–53.
https://doi.org/10.1109/access.2025.3648056.'
ieee: 'M. Meyer, D. R. Zapata Gonzalez, S. B. Kaltenpoth, and O. Müller, “Benchmarking
Time Series Foundation Models for Short-Term Household Electricity Load Forecasting,”
IEEE Access, vol. 13, pp. 218141–218153, 2025, doi: 10.1109/access.2025.3648056.'
mla: Meyer, Marcel, et al. “Benchmarking Time Series Foundation Models for Short-Term
Household Electricity Load Forecasting.” IEEE Access, vol. 13, Institute
of Electrical and Electronics Engineers (IEEE), 2025, pp. 218141–53, doi:10.1109/access.2025.3648056.
short: M. Meyer, D.R. Zapata Gonzalez, S.B. Kaltenpoth, O. Müller, IEEE Access 13
(2025) 218141–218153.
date_created: 2026-03-09T16:58:28Z
date_updated: 2026-03-10T08:13:21Z
doi: 10.1109/access.2025.3648056
intvolume: ' 13'
language:
- iso: eng
page: 218141-218153
publication: IEEE Access
publication_identifier:
issn:
- 2169-3536
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Benchmarking Time Series Foundation Models for Short-Term Household Electricity
Load Forecasting
type: journal_article
user_id: '105120'
volume: 13
year: '2025'
...
---
_id: '61098'
author:
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Alexander Marcus
full_name: Skolik, Alexander Marcus
id: '92908'
last_name: Skolik
orcid: 0009-0006-2519-1765
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
citation:
ama: 'Kaltenpoth SB, Skolik AM, Müller O, Beverungen D. A Step Towards Cognitive
Automation: Integrating LLM Agents with Process Rules. In: Lecture Notes in
Computer Science. Springer Nature Switzerland; 2025. doi:10.1007/978-3-032-02867-9_19'
apa: 'Kaltenpoth, S. B., Skolik, A. M., Müller, O., & Beverungen, D. (2025).
A Step Towards Cognitive Automation: Integrating LLM Agents with Process Rules.
Lecture Notes in Computer Science. 23rd International Conference on Business
Process Management, Sevilla. https://doi.org/10.1007/978-3-032-02867-9_19'
bibtex: '@inproceedings{Kaltenpoth_Skolik_Müller_Beverungen_2025, place={Cham},
title={A Step Towards Cognitive Automation: Integrating LLM Agents with Process
Rules}, DOI={10.1007/978-3-032-02867-9_19},
booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland},
author={Kaltenpoth, Sascha Benjamin and Skolik, Alexander Marcus and Müller, Oliver
and Beverungen, Daniel}, year={2025} }'
chicago: 'Kaltenpoth, Sascha Benjamin, Alexander Marcus Skolik, Oliver Müller, and
Daniel Beverungen. “A Step Towards Cognitive Automation: Integrating LLM Agents
with Process Rules.” In Lecture Notes in Computer Science. Cham: Springer
Nature Switzerland, 2025. https://doi.org/10.1007/978-3-032-02867-9_19.'
ieee: 'S. B. Kaltenpoth, A. M. Skolik, O. Müller, and D. Beverungen, “A Step Towards
Cognitive Automation: Integrating LLM Agents with Process Rules,” presented at
the 23rd International Conference on Business Process Management, Sevilla, 2025,
doi: 10.1007/978-3-032-02867-9_19.'
mla: 'Kaltenpoth, Sascha Benjamin, et al. “A Step Towards Cognitive Automation:
Integrating LLM Agents with Process Rules.” Lecture Notes in Computer Science,
Springer Nature Switzerland, 2025, doi:10.1007/978-3-032-02867-9_19.'
short: 'S.B. Kaltenpoth, A.M. Skolik, O. Müller, D. Beverungen, in: Lecture Notes
in Computer Science, Springer Nature Switzerland, Cham, 2025.'
conference:
end_date: 2025-09-05
location: Sevilla
name: 23rd International Conference on Business Process Management
start_date: 2025-08-31
date_created: 2025-08-30T09:43:49Z
date_updated: 2025-08-30T09:50:22Z
doi: 10.1007/978-3-032-02867-9_19
language:
- iso: eng
place: Cham
publication: Lecture Notes in Computer Science
publication_identifier:
isbn:
- '9783032028662'
- '9783032028679'
issn:
- 0302-9743
- 1611-3349
publication_status: published
publisher: Springer Nature Switzerland
status: public
title: 'A Step Towards Cognitive Automation: Integrating LLM Agents with Process Rules'
type: conference
user_id: '92908'
year: '2025'
...
---
_id: '61160'
abstract:
- lang: eng
text: As a possible solution to the demographic change and the resulting
knowledge loss due to retirements in the Energy sector, this study aimed to develop
a generic pipeline to implement and evaluate proof-of-concepts (PoCs) for LLM-based
assistance systems in new domains. Our pipeline contains an LLM-based data generation
strategy based on documents, a retrieval-augmented generation (RAG) architecture
utilizing prompting techniques on existing German LLMs, and an LLM-based automatic
evaluation strategy. We leverage our pipeline to evaluate five LLMs using data
from a German DSO. We found that the Llama3 and the Mistral model are appropriately
aligned for the task. We plan to pilot the RAG architecture in the DSO's infrastructure
for future research and continuously research improvements using the generated
human demonstrations.
article_type: original
author:
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: Kaltenpoth SB, Müller O. Don’t Touch the Power Line - A Proof-of-Concept for
Aligned LLM-Based Assistance Systems to Support the Maintenance in the Electricity
Distribution System. ACM SIGEnergy Energy Informatics Review. 2025;4(4):16-22.
doi:10.1145/3717413.3717415
apa: Kaltenpoth, S. B., & Müller, O. (2025). Don’t Touch the Power Line - A
Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support the Maintenance
in the Electricity Distribution System. ACM SIGEnergy Energy Informatics Review,
4(4), 16–22. https://doi.org/10.1145/3717413.3717415
bibtex: '@article{Kaltenpoth_Müller_2025, title={Don’t Touch the Power Line - A
Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support the Maintenance
in the Electricity Distribution System}, volume={4}, DOI={10.1145/3717413.3717415},
number={4}, journal={ACM SIGEnergy Energy Informatics Review}, publisher={Association
for Computing Machinery (ACM)}, author={Kaltenpoth, Sascha Benjamin and Müller,
Oliver}, year={2025}, pages={16–22} }'
chicago: 'Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Don’t Touch the Power
Line - A Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support
the Maintenance in the Electricity Distribution System.” ACM SIGEnergy Energy
Informatics Review 4, no. 4 (2025): 16–22. https://doi.org/10.1145/3717413.3717415.'
ieee: 'S. B. Kaltenpoth and O. Müller, “Don’t Touch the Power Line - A Proof-of-Concept
for Aligned LLM-Based Assistance Systems to Support the Maintenance in the Electricity
Distribution System,” ACM SIGEnergy Energy Informatics Review, vol. 4,
no. 4, pp. 16–22, 2025, doi: 10.1145/3717413.3717415.'
mla: Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Don’t Touch the Power Line
- A Proof-of-Concept for Aligned LLM-Based Assistance Systems to Support the Maintenance
in the Electricity Distribution System.” ACM SIGEnergy Energy Informatics Review,
vol. 4, no. 4, Association for Computing Machinery (ACM), 2025, pp. 16–22, doi:10.1145/3717413.3717415.
short: S.B. Kaltenpoth, O. Müller, ACM SIGEnergy Energy Informatics Review 4 (2025)
16–22.
date_created: 2025-09-09T12:30:30Z
date_updated: 2025-09-09T12:31:07Z
doi: 10.1145/3717413.3717415
intvolume: ' 4'
issue: '4'
language:
- iso: eng
page: 16-22
publication: ACM SIGEnergy Energy Informatics Review
publication_identifier:
issn:
- 2770-5331
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Don't Touch the Power Line - A Proof-of-Concept for Aligned LLM-Based Assistance
Systems to Support the Maintenance in the Electricity Distribution System
type: journal_article
user_id: '50640'
volume: 4
year: '2025'
...
---
_id: '54446'
abstract:
- lang: eng
text: 'ZusammenfassungVerteilnetzbetreiber in Deutschland
stehen vor großen Herausforderungen bei dem Management ihres unternehmensspezifischen
Wissens: Mitarbeiterengpässe durch den demographischen Wandel, Wissen ist nur
implizit vorhanden und nicht in Wissensmanagementsystemen digitalisiert, teilweise
gibt es gar keine Wissensmanagementsysteme oder Konzepte und das Verteilnetz wird
immer komplexer. Verbunden mit zunehmender Belastung von zentralen Komponenten
im Verteilnetz durch die Energiewende bedarf es neuer Lösungen, besonders für
die wissensintensiven Wartungs- und Instandhaltungsprozesse. Generative Artificial
Intelligence als aufstrebende Technologie, insb. durch Large Language Models,
zeigt hier erste Erfolge für die Anleitung, Entscheidungsunterstützung und den
Wissenstransfer. Aufbauend auf dem Design Science Research Forschungsparadigma
wird in diesem Beitrag ein ganzheitlicher Ansatz des Wissensmanagements konzipiert,
welcher als zentrale Komponente auf einem Assistenzsystem basiert. Ein Large Language
Model generiert Hilfestellungen für Netzmonteure während der Wartung und Instandhaltung
auf Basis von Anleitungen. Neben der Konzeption zeigt dieser Beitrag auch die
erarbeitete Strategie zur Demonstration und zukünftigen Evaluation der Ergebnisse.
Der Beitrag liefert ein für Verteilnetzbetreiber neuartiges Konzept Large Language
Model basierter Assistenzsysteme zum Wissensmanagement und zeigt zudem nachgelagerte
Schritte auf, die vor einer Markteinführung notwendig sind.'
author:
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
citation:
ama: zur Heiden P, Kaltenpoth SB. Knowledge Management for Service and Maintenance
on the Distribution Grid—Conceptualizing an Assistance System based on a Large
Language Model Wissensmanagement für Wartung und Instandhaltung im Verteilnetz –
Konzeption eines Assistenzsystems basierend auf einem Large Language Model. HMD
Praxis der Wirtschaftsinformatik. Published online 2024. doi:10.1365/s40702-024-01074-3
apa: zur Heiden, P., & Kaltenpoth, S. B. (2024). Knowledge Management for Service
and Maintenance on the Distribution Grid—Conceptualizing an Assistance System
based on a Large Language Model Wissensmanagement für Wartung und Instandhaltung
im Verteilnetz – Konzeption eines Assistenzsystems basierend auf einem Large Language
Model. HMD Praxis der Wirtschaftsinformatik. https://doi.org/10.1365/s40702-024-01074-3
bibtex: '@article{zur Heiden_Kaltenpoth_2024, title={Knowledge Management for Service
and Maintenance on the Distribution Grid—Conceptualizing an Assistance System
based on a Large Language Model Wissensmanagement für Wartung und Instandhaltung
im Verteilnetz – Konzeption eines Assistenzsystems basierend auf einem Large Language
Model}, DOI={10.1365/s40702-024-01074-3},
journal={HMD Praxis der Wirtschaftsinformatik}, publisher={Springer Fachmedien
Wiesbaden GmbH}, author={zur Heiden, Philipp and Kaltenpoth, Sascha Benjamin},
year={2024} }'
chicago: Heiden, Philipp zur, and Sascha Benjamin Kaltenpoth. “Knowledge Management
for Service and Maintenance on the Distribution Grid—Conceptualizing an Assistance
System based on a Large Language Model Wissensmanagement für Wartung und Instandhaltung
im Verteilnetz – Konzeption eines Assistenzsystems basierend auf einem Large Language
Model.” HMD Praxis der Wirtschaftsinformatik, 2024. https://doi.org/10.1365/s40702-024-01074-3.
ieee: 'P. zur Heiden and S. B. Kaltenpoth, “Knowledge Management for Service and
Maintenance on the Distribution Grid—Conceptualizing an Assistance System based
on a Large Language Model Wissensmanagement für Wartung und Instandhaltung im
Verteilnetz – Konzeption eines Assistenzsystems basierend auf einem Large Language
Model,” HMD Praxis der Wirtschaftsinformatik, 2024, doi: 10.1365/s40702-024-01074-3.'
mla: zur Heiden, Philipp, and Sascha Benjamin Kaltenpoth. “Knowledge Management
for Service and Maintenance on the Distribution Grid—Conceptualizing an Assistance
System based on a Large Language Model Wissensmanagement für Wartung und Instandhaltung
im Verteilnetz – Konzeption eines Assistenzsystems basierend auf einem Large Language
Model.” HMD Praxis der Wirtschaftsinformatik, Springer Fachmedien Wiesbaden
GmbH, 2024, doi:10.1365/s40702-024-01074-3.
short: P. zur Heiden, S.B. Kaltenpoth, HMD Praxis der Wirtschaftsinformatik (2024).
date_created: 2024-05-24T13:36:55Z
date_updated: 2024-08-16T11:05:12Z
doi: 10.1365/s40702-024-01074-3
language:
- iso: ger
publication: HMD Praxis der Wirtschaftsinformatik
publication_identifier:
issn:
- 1436-3011
- 2198-2775
publication_status: published
publisher: Springer Fachmedien Wiesbaden GmbH
status: public
title: Knowledge Management for Service and Maintenance on the Distribution Grid—Conceptualizing
an Assistance System based on a Large Language Model Wissensmanagement für Wartung
und Instandhaltung im Verteilnetz – Konzeption eines Assistenzsystems basierend
auf einem Large Language Model
type: journal_article
user_id: '64394'
year: '2024'
...
---
_id: '55500'
author:
- first_name: Ralf
full_name: Gitzel, Ralf
last_name: Gitzel
- first_name: Martin
full_name: Hoffmann, Martin
last_name: Hoffmann
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Alexander Marcus
full_name: Skolik, Alexander Marcus
id: '92908'
last_name: Skolik
orcid: 0009-0006-2519-1765
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Cansu
full_name: Kanak, Cansu
last_name: Kanak
- first_name: Kajan
full_name: Kandiah, Kajan
last_name: Kandiah
- first_name: Max-Ferdinand
full_name: Stroh, Max-Ferdinand
last_name: Stroh
- first_name: Wolfgang
full_name: Boos, Wolfgang
last_name: Boos
- first_name: Maurizio
full_name: Zajadatz, Maurizio
last_name: Zajadatz
- first_name: Michael
full_name: Suriyah, Michael
last_name: Suriyah
- first_name: Thomas
full_name: Leibfried, Thomas
last_name: Leibfried
- first_name: Dhruv Suresh
full_name: Singhal, Dhruv Suresh
last_name: Singhal
- first_name: Moritz
full_name: Bürger, Moritz
last_name: Bürger
- first_name: Dennis
full_name: Hunting, Dennis
last_name: Hunting
- first_name: Alexander
full_name: Rehmer, Alexander
last_name: Rehmer
- first_name: Aydin
full_name: Boyaci, Aydin
last_name: Boyaci
citation:
ama: Gitzel R, Hoffmann M, zur Heiden P, et al. Towards Cognitive Assistance and
Prognosis Systems in Power Distribution Grids – Open Issues, Suitable Technologies,
and Implementation Concepts. IEEE Access. Published online 2024:1-1. doi:10.1109/access.2024.3437195
apa: Gitzel, R., Hoffmann, M., zur Heiden, P., Skolik, A. M., Kaltenpoth, S. B.,
Müller, O., Kanak, C., Kandiah, K., Stroh, M.-F., Boos, W., Zajadatz, M., Suriyah,
M., Leibfried, T., Singhal, D. S., Bürger, M., Hunting, D., Rehmer, A., &
Boyaci, A. (2024). Towards Cognitive Assistance and Prognosis Systems in Power
Distribution Grids – Open Issues, Suitable Technologies, and Implementation Concepts.
IEEE Access, 1–1. https://doi.org/10.1109/access.2024.3437195
bibtex: '@article{Gitzel_Hoffmann_zur Heiden_Skolik_Kaltenpoth_Müller_Kanak_Kandiah_Stroh_Boos_et
al._2024, title={Towards Cognitive Assistance and Prognosis Systems in Power Distribution
Grids – Open Issues, Suitable Technologies, and Implementation Concepts}, DOI={10.1109/access.2024.3437195},
journal={IEEE Access}, publisher={Institute of Electrical and Electronics Engineers
(IEEE)}, author={Gitzel, Ralf and Hoffmann, Martin and zur Heiden, Philipp and
Skolik, Alexander Marcus and Kaltenpoth, Sascha Benjamin and Müller, Oliver and
Kanak, Cansu and Kandiah, Kajan and Stroh, Max-Ferdinand and Boos, Wolfgang and
et al.}, year={2024}, pages={1–1} }'
chicago: Gitzel, Ralf, Martin Hoffmann, Philipp zur Heiden, Alexander Marcus Skolik,
Sascha Benjamin Kaltenpoth, Oliver Müller, Cansu Kanak, et al. “Towards Cognitive
Assistance and Prognosis Systems in Power Distribution Grids – Open Issues, Suitable
Technologies, and Implementation Concepts.” IEEE Access, 2024, 1–1. https://doi.org/10.1109/access.2024.3437195.
ieee: 'R. Gitzel et al., “Towards Cognitive Assistance and Prognosis Systems
in Power Distribution Grids – Open Issues, Suitable Technologies, and Implementation
Concepts,” IEEE Access, pp. 1–1, 2024, doi: 10.1109/access.2024.3437195.'
mla: Gitzel, Ralf, et al. “Towards Cognitive Assistance and Prognosis Systems in
Power Distribution Grids – Open Issues, Suitable Technologies, and Implementation
Concepts.” IEEE Access, Institute of Electrical and Electronics Engineers
(IEEE), 2024, pp. 1–1, doi:10.1109/access.2024.3437195.
short: R. Gitzel, M. Hoffmann, P. zur Heiden, A.M. Skolik, S.B. Kaltenpoth, O. Müller,
C. Kanak, K. Kandiah, M.-F. Stroh, W. Boos, M. Zajadatz, M. Suriyah, T. Leibfried,
D.S. Singhal, M. Bürger, D. Hunting, A. Rehmer, A. Boyaci, IEEE Access (2024)
1–1.
date_created: 2024-08-05T05:54:36Z
date_updated: 2024-08-16T11:04:56Z
doi: 10.1109/access.2024.3437195
language:
- iso: eng
page: 1-1
project:
- _id: '650'
call_identifier: 7. Energieforschungsprogramm, Förderbereich "Digitalisierung der
Energiewende"
grant_number: 03E16090E
name: 'AProSys: AProSys -KI-gestützte Assistenz- und Prognosesysteme für den nachhaltigen
Einsatz in der intelligenten Verteilnetztechnik'
publication: IEEE Access
publication_identifier:
issn:
- 2169-3536
publication_status: published
publisher: Institute of Electrical and Electronics Engineers (IEEE)
status: public
title: Towards Cognitive Assistance and Prognosis Systems in Power Distribution Grids
– Open Issues, Suitable Technologies, and Implementation Concepts
type: journal_article
user_id: '64394'
year: '2024'
...
---
_id: '56945'
abstract:
- lang: eng
text: Adopting Large language models (LLMs) in organizations potentially revolutionizes
our lives and work. However, they can generate off-topic, discriminating, or harmful
content. This AI alignment problem often stems from misspecifications during the
LLM adoption, unnoticed by the principal due to the LLM’s black-box nature. While
various research disciplines investigated AI alignment, they neither address the
information asymmetries between organizational adopters and black-box LLM agents
nor consider organizational AI adoption processes. Therefore, we propose LLM ATLAS
(LLM Agency Theory-Led Alignment Strategy) a conceptual framework grounded in
agency (contract) theory, to mitigate alignment problems during organizational
LLM adoption. We conduct a conceptual literature analysis using the organizational
LLM adoption phases and the agency theory as concepts. Our approach results in
(1) providing an extended literature analysis process specific to AI alignment
methods during organizational LLM adoption and (2) providing a first LLM alignment
problem-solutionspace.
author:
- first_name: Sascha Benjamin
full_name: Kaltenpoth, Sascha Benjamin
id: '50640'
last_name: Kaltenpoth
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Kaltenpoth SB, Müller O. Getting in Contract with Large Language Models -
An Agency Theory Perspective On Large Language Model Alignment. In: Wirtschaftsinformatik
2024 Proceedings. ; 2024.'
apa: Kaltenpoth, S. B., & Müller, O. (2024). Getting in Contract with Large
Language Models - An Agency Theory Perspective On Large Language Model Alignment.
Wirtschaftsinformatik 2024 Proceedings.
bibtex: '@inproceedings{Kaltenpoth_Müller_2024, title={Getting in Contract with
Large Language Models - An Agency Theory Perspective On Large Language Model Alignment},
booktitle={Wirtschaftsinformatik 2024 Proceedings}, author={Kaltenpoth, Sascha
Benjamin and Müller, Oliver}, year={2024} }'
chicago: Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Getting in Contract with
Large Language Models - An Agency Theory Perspective On Large Language Model Alignment.”
In Wirtschaftsinformatik 2024 Proceedings, 2024.
ieee: S. B. Kaltenpoth and O. Müller, “Getting in Contract with Large Language Models
- An Agency Theory Perspective On Large Language Model Alignment,” 2024.
mla: Kaltenpoth, Sascha Benjamin, and Oliver Müller. “Getting in Contract with Large
Language Models - An Agency Theory Perspective On Large Language Model Alignment.”
Wirtschaftsinformatik 2024 Proceedings, 2024.
short: 'S.B. Kaltenpoth, O. Müller, in: Wirtschaftsinformatik 2024 Proceedings,
2024.'
conference:
end_date: 19.09.2024
start_date: 16.09.2024
date_created: 2024-11-07T16:23:23Z
date_updated: 2024-11-11T16:45:34Z
department:
- _id: '196'
language:
- iso: eng
main_file_link:
- url: https://aisel.aisnet.org/wi2024/91/
publication: Wirtschaftsinformatik 2024 Proceedings
status: public
title: Getting in Contract with Large Language Models - An Agency Theory Perspective
On Large Language Model Alignment
type: conference
user_id: '50640'
year: '2024'
...