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Publikationen

Ausgewählte Publikationen von Wissenschaftler*innen aus FAITH :

  • Dimitry Mindlin, Fabian Beer, Leonie Nora Sieger, Stefan Heindorf, Elena Esposito, Axel-Cyrille Ngonga Ngomo, Philipp Cimiano: Beyond one-shot explanations: a systematic literature review of dialogue-based xAI approaches. Artif. Intell. Rev. 58(3): 81 (2025).
  • Jan-Philipp Töberg, Axel-Cyrille Ngonga Ngomo, Michael Beetz, Philipp Cimiano: Commonsense knowledge in cognitive robotics: a systematic literature review. Frontiers Robotics AI 11 (2024).
  • Dimitry Mindlin, Amelie Sophie Robrecht, Michael Morasch, Philipp Cimiano: Measuring User Understanding in Dialogue-Based xAI Systems. ECAI 2024: 1148-1155.
  • Meisam Booshehri, Hendrik Buschmeier, Philipp Cimiano: A Model of Factors Contributing to the Success of Dialogical Explanations. ICMI 2024: 373-381.
  • Julia Becker, Mario Botsch, Philipp Cimiano, Melanie Derksen, Mohammad Fazleh Elahi, Angelika Maier, Marius Maile, Ingo Oliver Pätzold, Jonas Penningroth, Bettina Reglin, Markus Rothgänger, Silke Schwandt: Virtual Reality Based Access to Knowledge Graphs for History Research. SEMANTiCS 2023: 144-160.
  • Pöppel, J., Kahl, S., & Kopp, S. (2021). Resonating Minds—Emergent Collaboration Through Hierarchical Active Inference. Cognitive Computation, 14(2), 581–601. https://doi.org/10.1007/s12559-021-09960-4.
  • Kulms, P., & Kopp, S. (2018). A social cognition perspective on human--computer trust. The effect of perceived warmth and competence on trust in decision-making with computers. Frontiers in Digital Humanities. Human-Media Interaction, 5, 14. doi:10.3389/fdigh.2018.00014.
  • Pöppel, J., & Kopp, S. (2018). Satisficing Models of Bayesian Theory of Mind for Explaining Behavior of Differently Uncertain Agents. Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2018).
  • Hellwig, P., Buchholz, V., Kopp, S., & Maier, G. W. (2023). Let the user have a say - voice in automated decision-making. Computers in Human Behavior, 107446. https://doi.org/10.1016/j.chb.2022.107446.
  • Rohlfing, K., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., et al. (2021). Explanation as a social practice: Toward a conceptual framework for the social design of AI systems. IEEE Transactions on Cognitive and Developmental Systems, 13(3), 717--728.
  • Buschmeier, H., & Kopp, S. (2018). Communicative listener feedback in human–agent interaction: Artificial speakers need to be attentive and adaptive. Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1213–1221.
  • Stange, S., Hassan, T., Schröder, F., Konkol, J., & Kopp, S. (2022). Self-Explaining Social Robots: An Explainable Behavior Generation Architecture for Human-Robot Interaction. Frontiers in Artificial Intelligence, 5, 866920. https://doi.org/10.3389/frai.2022.866920.
  • Sieker J, Junker S, Utescher R, et al. (2024). The Illusion of Competence: Evaluating the Effect of Explanations on Users' Mental Models of Visual Question Answering Systems. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 19459–19475.
  • Brinner MF, Zarrieß S, Heger T. (2024). Weakly Supervised Claim Localization in Scientific Abstracts. In: Cimiano P, Frank A, Kohlhase M, Stein B, eds. Robust Argumentation Machines, RATIO 2024. Lecture Notes in Artificial Intelligence. Vol 14638. Cham: Springer: 20-38.
  • Lachenmaier C, Lumer E, Buschmeier H, Zarrieß S. (2024). Towards understanding the entanglement of human stereotypes and system biases in human–robot interaction. In: Grollman D, Broadbent E, eds. Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 646–649.
  • Schüz S, Gatt A, Zarrieß S. (2023). Rethinking symbolic and visual context in Referring Expression Generation. Frontiers in Artificial Intelligence. 18.
  • Alaçam Ö, Hoeken S, Zarrieß S. (2024). Eyes Don`t Lie: Subjective Hate Annotation and Detection with Gaze. In: Al-Onaizan Y, Bansal M, Chen Y-N, eds. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 187-205.
  • Bödding, R., Schriek, S. A., & Maier, G. W. (2025). A systematic review and meta-analysis of mixed reality in vocational education and training: Examining behavioral, cognitive, and affective training outcomes and possible moderators. Virtual Reality , 29(44).
  • Masjutin, L., Bangemann, A., Reimann, L., & Maier, G. W. (2024). Fatigued individuals show increased conformity in virtual meetings. Scientific Reports, 14, 18807.
  • Masjutin, L., Laing, J. K., & Maier, G. W. (2022). Why do we follow robots? An experimental investigation of conformity with robot, human, and hybrid majorities. In Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction (p. 139–146).
  • Ötting, S. K., Masjutin, L., Steil, J. J., & Maier, G. W. (2022). Let's work together: A meta–analysis on robot design features that enable successful human–robot interaction at work. Human Factors, 6(4), 1027-1050.
  • Abendroth, A., & Reimann, M. (2024). Organisational inhibition and promotion of flexible working in digitalised work environments. New Technology, Work and Employment, 39(1), 39-62.
  • Abendroth, A., & Schwarz, A. (2023). Digital Communication and Work-Life Supportive Supervisor Behaviors in Europe. Social Inclusion, 11(4), 198-210.
  • Gensler, E., Iseke, A., & Abendroth, A. (2025). How Algorithmic Direction Affects Work Autonomy Within Varying Control Configurations: A Fuzzy-Set Qualitative Comparative Analysis. management revue, 35(4), 442-468. 
  • Marx, C. K., Abendroth, A., Meyer, S. - C., Reimann, M., & Tisch, A. (2022). Measuring Digital Work in (German) Employee Surveys: An Overview and Proposal of Systematization. Journal of Contextual Economics, 142(1)
  • Scharf, N., Lükemann, L., Schubert, P., Williams, S., Abendroth, A., & Schwarz, A. (2023). Is the Structure of “Regular Working Days” about to Dissolve? Changes in Employees’ Time-Use Patterns Working in Enterprise Collaboration Systems During the COVID-19 Pandemic. Procedia Computer Science, 219, 431-438.
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