@inproceedings{6184,
  author       = {Uphaus, Andreas and Kampe, Tim},
  booktitle    = {CARF Luzern 2025: Controlling. Accounting. Risiko. Finanzen.},
  editor       = {Behringer, Stefan},
  isbn         = {978-3-907379-60-8},
  keywords     = {Künstliche Intelligenz, Large language models, Use Cases},
  location     = {Luzern},
  pages        = {180--195},
  publisher    = {Verlag IFZ - Hochschule Luzern},
  title        = {{Künstliche Intelligenz im Finanz- und Rechnungswesen von KMU und Familienunternehmen – Anwendungsfälle, Chancen und Risiken}},
  year         = {2025},
}

@inproceedings{6209,
  author       = {Matutat, André and Golin, Lena and Brandt-Pook, Hans},
  booktitle    = {INFORMATIK 2025},
  issn         = {2944-7682},
  keywords     = {Large Language Models, Retrieval-Augmented Generation, CO2-Bilanzierung, Tiefbau, Nachhaltigkeit, Assistenzsysteme, Wissensmanagement, Tool-Integration},
  location     = {Potsdam },
  number       = {366},
  pages        = {1345--1350},
  title        = {{LLM gesteuerte Planung zur Reduktion des CO2-Fußabdrucks im Tiefbau}},
  doi          = {10.18420/inf2025_119},
  year         = {2025},
}

@article{6244,
  author       = {Niederhaus, Marvin and Migenda, Nico and Weller, Julian and Kohlhase, Martin and Schenck, Wolfram},
  issn         = {2504-2289},
  journal      = {Big Data and Cognitive Computing},
  keywords     = {prescriptive analytics, prescriptive platforms, advanced data analytics, retrieval-augmented generation, graph-based retrieval-augmented generation, large language models, generative AI, genAI, recommender system},
  number       = {10},
  publisher    = {MDPI AG},
  title        = {{Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems}},
  doi          = {10.3390/bdcc9100261},
  volume       = {9},
  year         = {2025},
}