@inproceedings{AsBeMöMe35,
title = "Publishing a Chatbot: Opportunities and Challenges",
author = "Thomas Asselborn and Magnus Bender and Ralf M{\"o}ller and Sylvia Melzer",
year = "2025",
month = oct,
day = "8",
language = "English",
volume = "4058",
pages = "16--27",
booktitle = "CHAI+FCR 2025 Humanities-Centred Artificial Intelligence 2025 and Formal \& Cognitive Reasoning 2025",
publisher = "CEUR-WS.org",
note = "5th Workshop on Humanities-Centred AI (CHAI) ; Conference date: 16-09-2025",
url = "https://www.csmc.uni-hamburg.de/ki2025-chai",
}

@Article{app15105778,
AUTHOR = {Sievers, Thomas and Russwinkel, Nele},
TITLE = {Retrieving Memory Content from a Cognitive Architecture by Impressions from Language Models for Use in a Social Robot},
JOURNAL = {Applied Sciences},
VOLUME = {15},
YEAR = {2025},
NUMBER = {10},
ARTICLE-NUMBER = {5778},
URL = {https://www.mdpi.com/2076-3417/15/10/5778},
ISSN = {2076-3417},
ABSTRACT = {Large Language Models (LLMs) and Vision-Language Models (VLMs) have the potential to significantly advance the development and application of cognitive architectures for human–robot interaction (HRI) to enable social robots with enhanced cognitive capabilities. An essential cognitive ability of humans is the use of memory. We investigate a way to create a social robot with a human-like memory and recollection based on cognitive processes for a better comprehensible and situational behavior of the robot. Using a combined system consisting of an Adaptive Control of Thought-Rational (ACT-R) model and a humanoid social robot, we show how recollections from the declarative memory of the ACT-R model can be retrieved using data obtained by the robot via an LLM or VLM, processed according to the procedural memory of the cognitive model and returned to the robot as instructions for action. Real-world data captured by the robot can be stored as memory chunks in the cognitive model and recalled, for example by means of associations. This opens up possibilities for using human-like judgment and decision-making capabilities inherent in cognitive architectures with social robots and practically offers opportunities of augmenting the prompt for LLM-driven utterances with content from declarative memory, thus keeping them more contextually relevant. We illustrate the use of such an approach in HRI scenarios with the social robot Pepper.},
DOI = {10.3390/app15105778}
}

@INPROCEEDINGS{10871032,
  author={Sievers, Thomas},
  booktitle={2025 IEEE/SICE International Symposium on System Integration (SII)}, 
  title={Silence is Golden - Making Pauses in Human Utterances Comprehensible for Social Robots in Human-Robot Interaction *}, 
  year={2025},
  volume={},
  number={},
  pages={526-531},
  keywords={Sentiment analysis;Large language models;Social robots;System integration;Speech recognition;Chatbots;Text to speech},
  doi={10.1109/SII59315.2025.10871032}}

@inproceedings{heinrich2025towards,
  title={Towards a Bayesian Cognitive Model of Self-Belief Updating},
  author={Heinrich, Nils Wendel and von Engelhardt, Rebecca and {\"O}sterdiekhoff, Annika and Kopp, Stefan and Russwinkel, Nele},
  booktitle={Proceedings of International Conference on Cognitive Modeling (ICCM 2025)},
  year={2025}
}

@article{heinrich2025using,
  title={Using Eye Movements to Understand Sense of Control in Situated Action},
  author={Heinrich, Nils Wendel and {\"O}sterdiekhoff, Annika and Kopp, Stefan and Russwinkel, Nele},
  journal={Cognitive Science},
  volume={49},
  number={12},
  pages={e70154},
  year={2025},
  publisher={Wiley Online Library}
}

@inbook{AsBeMaMöMe25,
title = "Verbalisation Process of a RAG-Based Chatbot to Support Tabular Data Evaluation for Humanities Researchers",
author = "Thomas Asselborn and Magnus Bender and Florian Marwitz and Ralf M{\"o}ller and Sylvia Melzer",
year = "2025",
month = dec,
day = "22",
language = "English",
volume = "4140",
pages = "56--63",
editor = "Magnus Bender and Sylvia Melzer and Ralf M{\"o}ller and Stefan Thiemann",
booktitle = "Proceedings of the Workshop on Large Language Models for Research Data Management?! co-located with the INFORMATIK Festival 2025 (55th Annual Conference of the German Informatics Society), September 18, 2025, Potsdam, Germany (INFORMATIK FESTIVAL)",
publisher = "CEUR-WS.org",
note = "Large Language Models for Research Data Management?! ; Conference date: 18-09-2025 Through 18-09-2025",
url = "https://informatik2025.gi.de/workshops\_a-z.html, https://www.conferences.uni-hamburg.de/event/621/",

}

@inproceedings{LuBrMoGe24,
    author    = {Malte Luttermann and Tanya Braun and Ralf Möller and Marcel Gehrke},
    title     = {{Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs}},
    booktitle = {Proceedings of the Sixteenth International Conference on Scalable Uncertainty Management (SUM-2024)},
    year      = {2024},
    pages     = {265--280},
    publisher = {Springer},
}

@inproceedings{LuMaGe24b,
	author    = {Malte Luttermann and Johann Machemer and Marcel Gehrke},
	title     = {{Efficient Detection of Commutative Factors in Factor Graphs}},
	booktitle = {Proceedings of the Twelfth International Conference on Probabilistic Graphical Models (PGM-2024)},
	year      = {2024},
	volume    = {246},
	pages     = {38--56},
	publisher = {{PMLR}},
	url       = {https://proceedings.mlr.press/v246/luttermann24a.html}
}

@inproceedings{LuMoHa24,
    author    = {Malte Luttermann and Ralf Möller and Mattis Hartwig},
    title     = {{Towards Privacy-Preserving Relational Data Synthesis via Probabilistic Relational Models}},
    booktitle = {Proceedings of the Forty-Seventh German Conference on Artificial Intelligence (KI-2024)},
    year      = {2024},
    pages     = {175--189},
    publisher = {Springer}
}

@article{ScLuMo24,
  author    = {Tim Schulz and Malte Luttermann and Ralf Möller},
  title     = {AutoRAG: Grounding Text and Symbols},
  journal   = {German Journal of Artificial Intelligence},
  year      = {2024},
  publisher = {Springer},
  doi       = {https://doi.org/10.1007/s13218-024-00850-z}
}

@inproceedings{LuMaGe24,
  author    = {Malte Luttermann and Johann Machemer and Marcel Gehrke},
  title     = {Efficient Detection of Exchangeable Factors in Factor Graphs},
  booktitle = {Proceedings of the Thirty-Seventh International FLAIRS Conference (FLAIRS-24)},
  year      = {2024},
  volume    = {37},
  publisher = {Florida Online Journals},
  url       = {https://journals.flvc.org/FLAIRS/article/view/135518},
}

@article{LuBaBoGeGrMaScTeRoMo24,
  author    = {Malte Luttermann and Edgar Baake and Juljan Bouchagiar and Benjamin Gebel and Philipp Grüning and Dilini Manikwadura and Franziska Schollemann and Elisa Teifke and Philipp Rostalski and Ralf Möller},
  title     = {Automated Computation of Therapies Using Failure Mode and Effects Analysis in the Medical Domain},
  journal   = {German Journal of Artificial Intelligence},
  year      = {2024},
  publisher = {Springer},
  doi       = {https://doi.org/10.1007/s13218-023-00810-z}
}

@inproceedings{LuHaBrMoGe24,
  author    = {Malte Luttermann and Mattis Hartwig and Tanya Braun and Ralf Möller and Marcel Gehrke},
  title     = {Lifted Causal Inference in Relational Domains},
  booktitle = {Proceedings of the Third Conference on Causal Learning and Reasoning (CLeaR-24)},
  year      = {2024},
  volume    = {236},
  pages     = {827--842},
  publisher = {PMLR},
  url       = {https://proceedings.mlr.press/v236/luttermann24a.html},
}

@inproceedings{BaMaTa24,
    author    = {Max Bannach, Florian Andreas Marwitz and Till Tantau},
    title     = {{ Faster Graph Algorithms Through DAG Compression}},
    booktitle = {Proceedings of the 41st International Symposium on Theoretical Aspects of Computer Science (STACS 2024)},
    year      = {2024},
    pages     = {},
    publisher = {},
    url = {}
}

@inproceedings{LuBrMoGe24,
    author    = {Malte Luttermann and Tanya Braun and Ralf M\"oller and Marcel Gehrke},
    title     = {{Colour Passing Revisited: Lifted Model Construction with Commutative Factors}},
    booktitle = {Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence     (AAAI-24)},
    year      = {2024},
    volume    = {38},
    pages     = {20500--20507},
    publisher = {{AAAI} Press},
    doi       = {https://doi.org/10.1609/aaai.v38i18.30034},
}