Publikationen
Alle Publikationen
2025
Schulz, C. (n.d.). Feeds. Ein zentrales Strukturprinzip sozialer Medien. In R. Dörre & A. Tuschling (Eds.), Handbuch Social Media: Geschichte – Kultur – Ästhetik (1st ed.). Metzler Verlag.
2024
Lammert, O., Richter, B., Schütze, C., Thommes, K., & Wrede, B. (2024). Humans in XAI: Increased Reliance in Decision-Making Under Uncertainty by Using Explanation Strategies. Frontiers in Behavioral Economics. https://doi.org/10.3389/frbhe.2024.1377075
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence, 38(13), 14388–14396. https://doi.org/10.1609/aaai.v38i13.29352
Banh, N. C., & Scharlau, I. (2024). Effects of task difficulty on visual processing speed. Tagung experimentell arbeitender Psycholog:innen (TeaP), Regensburg.
Stratmann, L., Banh, N. C., Scharlau, I., & Dressler, F. (2024). Safety Assistance Systems for Bicyclists: Toward Empirical Studies of the Dooring Problem. ACM Symposium on Principles of Distributed Computing (PODC 2024), Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED 2024). https://doi.org/10.1145/3663338.3665831
Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190
Schulz, C. (2024). Vernakulärer Code oder die Geister, die der Algorithmus rief - digitale Schriftlichkeit im Kontext von sozialen Medienplattformen. In M. Bartelmus & A. Nebrig (Eds.), Digitale Schriftlichkeit – Progammieren, Prozessieren und Codieren von Schrift (1st ed.). transcript . https://doi.org/10.1515/9783839468135-009
Schulz, C. (n.d.). Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung sozialmedialer Infrastruktur aus dem Geiste der Fotografie. In A. Schürmann & K. Yacavone (Eds.), Die Fotografie und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut (1st ed.). Reimer Verlag.
Schulz, C. (n.d.). On “Super Likes” and Algorithmic (In)Visibilities: Frictions Between Social and Economic Logics in the Context of Social Media Platforms. Digital Culture & Society , 2.
Robrecht, A., Voss, H., Gottschalk, L., & Kopp, S. (2024). Integrating Representational Gestures into Automatically Generated Embodied Explanations and its Effects on Understanding and Interaction Quality. In arXiv:2406.12544.
Kolpaczki, P., Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. In S. Dasgupta, S. Mandt, & Y. Li (Eds.), Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (Vol. 238, pp. 3520–3528). PMLR.
Thommes, K., Lammert, O., Schütze, C., Richter, B., & Wrede, B. (2024). Human Emotions in AI Explanations. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-031-63803-9_15
Beierling, H., & Vollmer, A.-L. (2024). The Power of Combined Modalities in Interactive Robot Learning. In arXiv:2405.07817.
Beierling, H., Loos, K., Helmert, R., & Vollmer, A.-L. (2024). Advancing Human-Robot Collaboration: The Impact of Flexible Input Mechanisms. Robotics: Science and Systems, Delf.
Sengupta, M., El Baff, R., Alshomary, M., & Wachsmuth, H. (2024). Analyzing the Use of Metaphors in News Editorials for Political Framing. In K. Duh, H. Gomez, & S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 3621–3631). Association for Computational Linguistics.
Alshomary, M., Lange, F., Booshehri, M., Sengupta, M., Cimiano, P., & Wachsmuth, H. (2024). Modeling the Quality of Dialogical Explanations. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 11523–11536). ELRA and ICCL.
Alpsancar, S. (2024). Warum und wozu erklärbare KI? Über die Verschiedenheit dreier paradigmatischer Zwecksetzungen. In R. Adolphi, S. Alpsancar, S. Hahn, & M. Kettner (Eds.), Philosophische Digitalisierungsforschung Verantwortung, Verständigung, Vernunft, Macht (pp. 55–113). transcript.
Türk, O., Lazarov, S., Wang, Y., Buschmeier, H., Grimminger, A., & Wagner, P. (n.d.). Predictability of understanding in explanatory interactions based on multimodal cues. Proceedings of the 26th ACM International Conference on Multimodal Interaction. The 26th ACM International Conference on Multimodal Interaction, San José, Costa Rica. https://doi.org/10.1145/3678957.3685741
Wang, Y., Xu, Y., Skantze, G., & Buschmeier, H. (2024). How much does nonverbal communication conform to entropy rate constancy?: A case study on listener gaze in interaction. Findings of the Association for Computational Linguistics ACL 2024, 3533–3545.
Booshehri, M., Buschmeier, H., & Cimiano, P. (n.d.). A model of factors contributing to the success of dialogical explanations. Proceedings of the 26th ACM International Conference on Multimodal Interaction. 26th ACM International Conference on Multimodal Interaction, San José, Costa Rica. https://doi.org/10.1145/3678957.3685744
Battefeld, D., Mues, S., Wehner, T., House, P., Kellinghaus, C., Wellmer, J., & Kopp, S. (2024). Revealing the Dynamics of Medical Diagnostic Reasoning as Step-by-Step Cognitive Process Trajectories. Proceedings of the 46th Annual Conference of the Cognitive Science Society. The Annual Meeting of the Cognitive Science Society, Rotterdam, NL.
Alpsancar, S., Matzner, T., & Philippi, M. (2024). Unpacking the purposes of explainable AI. Smart Ethics in the Digital World: Proceedings of the ETHICOMP 2024. 21th International Conference on the Ethical and Social Impacts of ICT, 31–35.
Wagner, P., Włodarczak, M., Buschmeier, H., Türk, O., & Gilmartin, E. (2024). Turn-taking dynamics across different phases of explanatory dialogues. Proceedings of the 28th Workshop on the Semantics and Pragmatics of Dialogue, 6–14.
Buhl, H. M., Fischer , J. B., & Rohlfing, K. (2024). Changes in partner models – Effects of adaptivity in the course of explanations. Proceedings of the Annual Meeting of the Cognitive Science Society, 46.
Klowait, N., Erofeeva, M., Lenke, M., Horwath, I., & Buschmeier, H. (2024). Can AI explain AI? Interactive co-construction of explanations among human and artificial agents. Discourse & Communication, 18(6). https://doi.org/10.1177/17504813241267069
Pilán, I., Prévot, L., Buschmeier, H., & Lison, P. (2024). Conversational feedback in scripted versus spontaneous dialogues: A comparative analysis. Proceedings of the 25th Meeting of the Special Interest Group on Discourse and Dialogue, 440–457. https://doi.org/10.18653/v1/2024.sigdial-1.38
Booshehri, M., Buschmeier, H., Cimiano, P., Kopp, S., Kornowicz, J., Lammert, O., Matarese, M., Mindlin, D., Robrecht, A. S., Vollmer, A.-L., Wagner, P., & Wrede, B. (2024). Towards a Computational Architecture for Co-Constructive Explainable Systems. Proceedings of the 2024 Workshop on Explainability Engineering, 20–25. https://doi.org/10.1145/3648505.3648509
Booshehri, M., Buschmeier, H., & Cimiano, P. (n.d.). Towards a BFO-based ontology of understanding in explanatory interactions. Proceedings of the 4th International Workshop on Data Meets Applied Ontologies in Explainable AI (DAO-XAI). 4th International Workshop on Data Meets Applied Ontologies in Explainable AI (DAO-XAI), Santiago de Compostela, Spain.
Riechmann, A. N., & Buschmeier, H. (2024). Automatic reconstruction of dialogue participants’ coordinating gaze behavior from multiple camera perspectives. Book of Abstracts of the 2nd International Multimodal Communication Symposium, 38–39.
Liedeker, F., Sanchez-Graillet, O., Seidler, M., Brandt, C., Wellmer, J., & Cimiano, P. (n.d.). A User Study Evaluating Argumentative Explanations in Diagnostic Decision Support. First Workshop on Natural Language Argument-Based Explanations, Santiago de Compostela, Spain.
Liedeker, F., Düsing, C., Nieveler, M., & Cimiano, P. (2024). An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity. 2nd World Conference on eXplainable Artificial Intelligence, Valetta, Malta.
Battefeld, D., Liedeker, F., Cimiano, P., & Kopp, S. (2024). ASCODI: An XAI-based interactive reasoning support system for justifiable medical diagnosing. Proceedings of the 1st Workshop on Multimodal, Affective and Interactive EXplainable AI (MAI-XAI). European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, Spain.
Singh, A., & Rohlfing, K. J. (2024). Coupling of Task and Partner Model: Investigating the Intra-Individual Variability in Gaze during Human–Robot Explanatory Dialogue. Proceedings of 26th ACM International Conference on Multimodal Interaction (ICMI 2024). 26th ACM International Conference on Multimodal Interaction (ICMI 2024), San Jose, Costa Rica. https://doi.org/10.1145/3686215.3689202
2023
Rautenberg, F., Kuhlmann, M., Wiechmann, J., Seebauer, F., Wagner, P., & Haeb-Umbach, R. (2023). On Feature Importance and Interpretability of Speaker Representations. ITG Conference on Speech Communication. ITG Conference on Speech Communication, Aachen.
Wiechmann, J., Rautenberg, F., Wagner, P., & Haeb-Umbach, R. (2023). Explaining voice characteristics to novice voice practitioners-How successful is it? 20th International Congress of the Phonetic Sciences (ICPhS) .
Lebedeva, A., Kornowicz, J., Lammert, O., & Papenkordt, J. (2023). The Role of Response Time for Algorithm Aversion in Fast and Slow Thinking Tasks. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_9
Peters, T. M., & Visser, R. W. (2023). The Importance of Distrust in AI. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-031-44070-0_15
Seebauer, F., Kuhlmann, M., Haeb-Umbach, R., & Wagner, P. (2023). Re-examining the quality dimensions of synthetic speech. 12th Speech Synthesis Workshop (SSW) 2023.
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning. https://doi.org/10.1007/s10994-023-06385-y
Artelt, A., Visser, R., & Hammer, B. (2023). “I do not know! but why?” — Local model-agnostic example-based explanations of reject. Neurocomputing, 558, Article 126722. https://doi.org/10.1016/j.neucom.2023.126722
Reijers, W. (2023). Technology and Civic Virtue. Philosophy & Technology, 36(4), Article 71. https://doi.org/10.1007/s13347-023-00669-w
Kornowicz, J., & Thommes, K. (2023). Aggregating Human Domain Knowledge for Feature Ranking. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_7
Groß, A., Schütze, C., Brandt, M., Wrede, B., & Richter, B. (2023). RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research. Frontiers in Robotics and AI, 10. https://doi.org/10.3389/frobt.2023.1245501
Scharlau, I., & Karsten, A. (2023). Schreibfokussierte Graduiertenförderung: Reflexive Spezialisierung für interdisziplinäre Forschungskontexte. In B. Berendt, A. Fleischmann, G. Salmhofer, N. Schaper, B. Szczyrba, M. Wiemer, & J. Wildt (Eds.), Neues Handbuch Hochschullehre (Vol. 111, pp. 17–35). DUZ medienhaus.
Terfloth, L., Schaffer, M., Buhl, H. M., & Schulte, C. (2023). Adding Why to What? Analyses of an Everyday Explanation. 1st World Conference on eXplainable Artificial Intelligence (xAI 2023), Lisboa. https://doi.org/10.1007/978-3-031-44070-0_13
Alpsancar, S. (2023). What is AI Ethics? Ethics as means of self-regulation and the need for critical reflection . International Conference on Computer Ethics 2023, 1(1), 1--17.
Schulz, C. (2023). From mental models to algorithmic imaginaries to co-constructive mental models. Navigationen – Zeitschrift Für Medien- Und Kulturwissenschaften , 2, 65–75. http://dx.doi.org/10.25819/ubsi/10428
Schulz, C., & Schröter, J. (2023). Tech/Imaginations – Introduction. Navigationen – Zeitschrift Für Medien- Und Kulturwissenschaften , 2, 7–14. http://dx.doi.org/10.25819/ubsi/10428
Schulz, C. (2023). A new algorithmic imaginary. Media, Culture & Society, 45(3), 646–655. https://doi.org/10.1177/01634437221136014
Johnson, D., Hakobyan, O., & Drimalla, H. (2023). Towards Interpretability in Audio and Visual Affective Machine Learning: A Review.
Richter, B., Putze, F., Ivucic, G., Brandt, M., Schütze, C., Reisenhofer, R., Wrede, B., & Schultz, T. (2023). EEG Correlates of Distractions and Hesitations in Human–Robot Interaction: A LabLinking Pilot Study. Multimodal Technologies and Interaction, 7(4), Article 37. https://doi.org/10.3390/mti7040037
Robrecht, A., & Kopp, S. (2023). SNAPE: A Sequential Non-Stationary Decision Process Model for Adaptive Explanation Generation. Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 48–58. https://doi.org/10.5220/0011671300003393
Dyck, L., Beierling, H., Helmert, R., & Vollmer, A.-L. (2023). Technical Transparency for Robot Navigation Through AR Visualizations. Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, 720–724. https://doi.org/10.1145/3568294.3580181
Esposito, E. (2023). Does Explainability Require Transparency? Sociologica, 16(3), 17–27. https://doi.org/10.6092/ISSN.1971-8853/15804
Esposito, E. (2023). Explaining Machines: Social Management of Incomprehensible Algorithms. Introduction. Sociologica, 16(3), 1–4. https://doi.org/10.6092/ISSN.1971-8853/16265
Rautenberg, F., Kuhlmann, M., Ebbers, J., Wiechmann, J., Seebauer, F., Wagner, P., & Haeb-Umbach, R. (2023). Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics. Fortschritte Der Akustik - DAGA 2023, 1409–1412.
Hanselle, J., Kornowicz, J., Heid, S., Thommes, K., & Hüllermeier, E. (2023). Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain. Lernen, Wissen, Daten, Analysen (LWDA) Conference Proceedings. Lernen, Wissen, Daten, Analysen 2023, Marburg, Germany.
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2023). iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. In Machine Learning and Knowledge Discovery in Databases: Research Track. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43418-1_26
Muschalik, M., Fumagalli, F., Jagtani, R., Hammer, B., & Huellermeier, E. (2023). iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. In Communications in Computer and Information Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-44064-9_11
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning, 112(12), 4863–4903. https://doi.org/10.1007/s10994-023-06385-y
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). On Feature Removal for Explainability in Dynamic Environments. ESANN 2023 Proceedings. ESANN 2023 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (Belgium) and online. https://doi.org/10.14428/esann/2023.es2023-148
Fumagalli, F., Muschalik, M., Kolpaczki, P., Hüllermeier, E., & Hammer, B. (2023). SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NeurIPS 2023 - Advances in Neural Information Processing Systems, 36, 11515--11551.
Sengupta, M., Alshomary, M., Scharlau, I., & Wachsmuth, H. (2023). Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. Findings of the Association for Computational Linguistics: EMNLP 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.308
Sengupta, M., Alshomary, M., & Wachsmuth, H. (2023). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 3rd Workshop on Figurative Language Processing (FLP). https://doi.org/10.18653/v1/2022.flp-1.19
Klowait, N. (2023). On the Multimodal Resolution of a Search Sequence in Virtual Reality. Human Behavior and Emerging Technologies, 2023, 1–15. https://doi.org/10.1155/2023/8417012
Klowait, N., & Erofeeva, M. (2023). Halting the Decay of Talk. Social Interaction. Video-Based Studies of Human Sociality, 6(1). https://doi.org/10.7146/si.v6i1.136903
Banh, N. C., & Scharlau, I. (2023). First steps towards real-time assessment of attentional weights and capacity according to TVA. In S. Merz, C. Frings, B. Leuchtenberg, B. Moeller, S. Mueller, R. Neumann, B. Pastötter, L. Pingen, & G. Schui (Eds.), Abstracts of the 65th TeaP. ZPID (Leibniz Institute for Psychology). https://doi.org/10.23668/PSYCHARCHIVES.12945
Groß, A., Singh, A., Banh, N. C., Richter, B., Scharlau, I., Rohlfing, K. J., & Wrede, B. (2023). Scaffolding the human partner by contrastive guidance in an explanatory human-robot dialogue. Frontiers in Robotics and AI, 10. https://doi.org/10.3389/frobt.2023.1236184
Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). Probabilistic Scoring Lists for Interpretable Machine Learning. In Discovery Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-45275-8_13
Tech/Imaginations. (2023). In C. Schulz, J. Schröter, & C. Ernst (Eds.), Navigationen – Zeitschrift für Medien- und Kulturwissenschaften (Vol. 2). Universi Verlag . http://dx.doi.org/10.25819/ubsi/10428
Schütze, C., Lammert, O., Richter, B., Thommes, K., & Wrede, B. (2023). Emotional Debiasing Explanations for Decisions in HCI. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_20
Robrecht, A., & Kopp, S. (2023). SNAPE: A Sequential Non-Stationary Decision Process Model for Adaptive Explanation Generation. Proceedings of the 15th International Conference on Agents and Artificial Intelligence. https://doi.org/10.5220/0011671300003393
Robrecht, A., Rothgänger, M., & Kopp, S. (2023). A Study on the Benefits and Drawbacks of Adaptivity in AI-generated Explanations. Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents. https://doi.org/10.1145/3570945.3607339
Fisher, J., Robrecht, A., Kopp, S., & Rohlfing, K. (2023). Exploring the Semantic Dialogue Patterns of Explanations – a Case Study of Game Explanations. Proceedings of the 27th Workshop on the Semantics and Pragmatics of Dialogue . Semdial, Maribor.
Buschmeier, H., Buhl, H. M., Kern, F., Grimminger, A., Beierling, H., Fisher, J., Groß, A., Horwath, I., Klowait, N., Lazarov, S., Lenke, M., Lohmer, V., Rohlfing, K., Scharlau, I., Singh, A., Terfloth, L., Vollmer, A.-L., Wang, Y., Wilmes, A., & Wrede, B. (2023). Forms of Understanding of XAI-Explanations. In arXiv:2311.08760.
Beierling, H., Richter, P., Brandt, M., Terfloth, L., Schulte, C., Wersing, H., & Vollmer, A.-L. (2023). What you need to know about a learning robot: Identifying the enabling architecture of complex systems. In arXiv:2311.14431.
Sengupta, M., Alshomary, M., Scharlau, I., & Wachsmuth, H. (2023). Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In H. Bouamor, J. Pino, & K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 4636–4659). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.308
Beer, F., & Schulz, C. (n.d.). The Return of Black Box Theory in Explainable AI. 4S Conference (Society for the Social Studies of Science), Honolulu/Hawaii, November 9.
Karsten, A. (2023). Voices in Dialogue: Taking Polyphony in Academic Writing Seriously. Written Communication, 41(1), 6–36. https://doi.org/10.1177/07410883231207104
Wang, Y., & Buschmeier, H. (2023). Does listener gaze in face-to-face interaction follow the Entropy Rate Constancy principle: An empirical study. Findings of the Association for Computational Linguistics: EMNLP 2023, 15372–15379.
Singh, A., & Rohlfing, K. J. (2023). Contrastiveness in the context of action demonstration: an eye-tracking study on its effects on action perception and action recall. Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45). 45th Annual Conference of the Cognitive Science Society, Sydney.
Liedeker, F., & Cimiano, P. (2023). A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations. xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lissabon.
Liedeker, F., & Cimiano, P. (2023). Dynamic Feature Selection in AI-based Diagnostic Decision Support for Epilepsy. 1st International Conference on Artificial Intelligence in Epilepsy and Neurological Disorders, Breckenridge, CO, USA .
Buschmeier, H., Buhl, H. M., Kern, F., Grimminger, A., Beierling, H., Fisher, J., Groß, A., Horwath, I., Klowait, N., Lazarov, S., Lenke, M., Lohmer, V., Rohlfing, K., Scharlau, I., Singh, A., Terfloth, L., Vollmer, A.-L., Wang, Y., Wilmes, A., & Wrede, B. (2023). Forms of Understanding of XAI-Explanations. In arXiv:2311.08760.
2022
Wiechmann, J., Glarner, T., Rautenberg, F., Wagner, P., & Haeb-Umbach, R. (2022). Technically enabled explaining of voice characteristics. 18. Phonetik Und Phonologie Im Deutschsprachigen Raum (P&P).
Schmid, U., & Wrede, B. (2022). What is Missing in XAI So Far? KI - Künstliche Intelligenz, 36(3–4), 303–315. https://doi.org/10.1007/s13218-022-00786-2
Schmid, U., & Wrede, B. (2022). Explainable AI. KI - Künstliche Intelligenz, 36(3–4), 207–210. https://doi.org/10.1007/s13218-022-00788-0
Wrede, B. (2022). AI: Back to the Roots? KI - Künstliche Intelligenz, 36(2), 117–120. https://doi.org/10.1007/s13218-022-00773-7
Fisher, J. B., Lohmer, V., Kern, F., Barthlen, W., Gaus, S., & Rohlfing, K. (2022). Exploring Monological and Dialogical Phases in Naturally Occurring Explanations. KI - Künstliche Intelligenz, 36(3–4), 317–326. https://doi.org/10.1007/s13218-022-00787-1
Rohlfing, K., Vollmer, A.-L., Fritsch, J., & Wrede, B. (2022). Which “motionese” parameters change with children’s age? Disentangling attention-getting from action-structuring modifications. Frontiers in Communication, 7. https://doi.org/10.3389/fcomm.2022.922405
Groß, A., Schütze, C., Wrede, B., & Richter, B. (2022). An Architecture Supporting Configurable Autonomous Multimodal Joint-Attention-Therapy for Various Robotic Systems. INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 154–159. https://doi.org/10.1145/3536220.3558070
Schütze, C., Groß, A., Wrede, B., & Richter, B. (2022). Enabling Non-Technical Domain Experts to Create Robot-Assisted Therapeutic Scenarios via Visual Programming. INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 166–170. https://doi.org/10.1145/3536220.3558072
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2022). Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz, 36(3–4), 211–224. https://doi.org/10.1007/s13218-022-00766-6
Sieger, L. N., Hermann, J., Schomäcker, A., Heindorf, S., Meske, C., Hey, C.-C., & Doğangün, A. (2022). User Involvement in Training Smart Home Agents. International Conference on Human-Agent Interaction. HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand. https://doi.org/10.1145/3527188.3561914
Finke, J., Horwath, I., Matzner, T., & Schulz, C. (2022). (De)Coding social practice in the field of XAI: Towards a co-constructive framework of explanations and understanding between lay users and algorithmic systems. Artificial Intelligence in HCI, 149–160. https://doi.org/10.1007/978-3-031-05643-7_10
Wachsmuth, H., & Alshomary, M. (2022). “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, & S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics (pp. 344–354). International Committee on Computational Linguistics.
Sengupta, M., Alshomary, M., & Wachsmuth, H. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 2022 Workshop on Figurative Language Processing.
Finke, J., Horwath, I., Matzner, T., & Schulz, C. (2022). (De)Coding Social Practice in the Field of XAI: Towards a Co-constructive Framework of Explanations and Understanding Between Lay Users and Algorithmic Systems. Artificial Intelligence in HCI, 149–160. https://doi.org/10.1007/978-3-031-05643-7_10
Banh, N. C., & Scharlau, I. (2022). Effects of verbal negation on TVA’s capacity and weight parameters. In S. Malejka, M. Barth, H. Haider, & C. Stahl (Eds.), TeaP 2022 - Abstracts of the 64th Conference of Experimental Psychologists . Pabst Science Publishers. https://doi.org/10.23668/psycharchives.5677
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Zeitschriftenartikel
2024
Lammert, O., Richter, B., Schütze, C., Thommes, K., & Wrede, B. (2024). Humans in XAI: Increased Reliance in Decision-Making Under Uncertainty by Using Explanation Strategies. Frontiers in Behavioral Economics. https://doi.org/10.3389/frbhe.2024.1377075
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence, 38(13), 14388–14396. https://doi.org/10.1609/aaai.v38i13.29352
Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190
Schulz, C. (n.d.). On “Super Likes” and Algorithmic (In)Visibilities: Frictions Between Social and Economic Logics in the Context of Social Media Platforms. Digital Culture & Society , 2.
Buhl, H. M., Fischer , J. B., & Rohlfing, K. (2024). Changes in partner models – Effects of adaptivity in the course of explanations. Proceedings of the Annual Meeting of the Cognitive Science Society, 46.
Klowait, N., Erofeeva, M., Lenke, M., Horwath, I., & Buschmeier, H. (2024). Can AI explain AI? Interactive co-construction of explanations among human and artificial agents. Discourse & Communication, 18(6). https://doi.org/10.1177/17504813241267069
2023
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning. https://doi.org/10.1007/s10994-023-06385-y
Artelt, A., Visser, R., & Hammer, B. (2023). “I do not know! but why?” — Local model-agnostic example-based explanations of reject. Neurocomputing, 558, Article 126722. https://doi.org/10.1016/j.neucom.2023.126722
Reijers, W. (2023). Technology and Civic Virtue. Philosophy & Technology, 36(4), Article 71. https://doi.org/10.1007/s13347-023-00669-w
Kornowicz, J., & Thommes, K. (2023). Aggregating Human Domain Knowledge for Feature Ranking. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_7
Groß, A., Schütze, C., Brandt, M., Wrede, B., & Richter, B. (2023). RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research. Frontiers in Robotics and AI, 10. https://doi.org/10.3389/frobt.2023.1245501
Schulz, C. (2023). From mental models to algorithmic imaginaries to co-constructive mental models. Navigationen – Zeitschrift Für Medien- Und Kulturwissenschaften , 2, 65–75. http://dx.doi.org/10.25819/ubsi/10428
Schulz, C., & Schröter, J. (2023). Tech/Imaginations – Introduction. Navigationen – Zeitschrift Für Medien- Und Kulturwissenschaften , 2, 7–14. http://dx.doi.org/10.25819/ubsi/10428
Schulz, C. (2023). A new algorithmic imaginary. Media, Culture & Society, 45(3), 646–655. https://doi.org/10.1177/01634437221136014
Richter, B., Putze, F., Ivucic, G., Brandt, M., Schütze, C., Reisenhofer, R., Wrede, B., & Schultz, T. (2023). EEG Correlates of Distractions and Hesitations in Human–Robot Interaction: A LabLinking Pilot Study. Multimodal Technologies and Interaction, 7(4), Article 37. https://doi.org/10.3390/mti7040037
Esposito, E. (2023). Does Explainability Require Transparency? Sociologica, 16(3), 17–27. https://doi.org/10.6092/ISSN.1971-8853/15804
Esposito, E. (2023). Explaining Machines: Social Management of Incomprehensible Algorithms. Introduction. Sociologica, 16(3), 1–4. https://doi.org/10.6092/ISSN.1971-8853/16265
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning, 112(12), 4863–4903. https://doi.org/10.1007/s10994-023-06385-y
Klowait, N. (2023). On the Multimodal Resolution of a Search Sequence in Virtual Reality. Human Behavior and Emerging Technologies, 2023, 1–15. https://doi.org/10.1155/2023/8417012
Klowait, N., & Erofeeva, M. (2023). Halting the Decay of Talk. Social Interaction. Video-Based Studies of Human Sociality, 6(1). https://doi.org/10.7146/si.v6i1.136903
Groß, A., Singh, A., Banh, N. C., Richter, B., Scharlau, I., Rohlfing, K. J., & Wrede, B. (2023). Scaffolding the human partner by contrastive guidance in an explanatory human-robot dialogue. Frontiers in Robotics and AI, 10. https://doi.org/10.3389/frobt.2023.1236184
Karsten, A. (2023). Voices in Dialogue: Taking Polyphony in Academic Writing Seriously. Written Communication, 41(1), 6–36. https://doi.org/10.1177/07410883231207104
2022
Schmid, U., & Wrede, B. (2022). What is Missing in XAI So Far? KI - Künstliche Intelligenz, 36(3–4), 303–315. https://doi.org/10.1007/s13218-022-00786-2
Schmid, U., & Wrede, B. (2022). Explainable AI. KI - Künstliche Intelligenz, 36(3–4), 207–210. https://doi.org/10.1007/s13218-022-00788-0
Wrede, B. (2022). AI: Back to the Roots? KI - Künstliche Intelligenz, 36(2), 117–120. https://doi.org/10.1007/s13218-022-00773-7
Fisher, J. B., Lohmer, V., Kern, F., Barthlen, W., Gaus, S., & Rohlfing, K. (2022). Exploring Monological and Dialogical Phases in Naturally Occurring Explanations. KI - Künstliche Intelligenz, 36(3–4), 317–326. https://doi.org/10.1007/s13218-022-00787-1
Rohlfing, K., Vollmer, A.-L., Fritsch, J., & Wrede, B. (2022). Which “motionese” parameters change with children’s age? Disentangling attention-getting from action-structuring modifications. Frontiers in Communication, 7. https://doi.org/10.3389/fcomm.2022.922405
Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2022). Agnostic Explanation of Model Change based on Feature Importance. KI - Künstliche Intelligenz, 36(3–4), 211–224. https://doi.org/10.1007/s13218-022-00766-6
Axelsson, A., Buschmeier, H., & Skantze, G. (2022). Modeling Feedback in Interaction With Conversational Agents—A Review. Frontiers in Computer Science, 4. https://doi.org/10.3389/fcomp.2022.744574
2021
Rohlfing, K. J., Cimiano, P., Scharlau, I., Matzner, T., Buhl, H. M., Buschmeier, H., Esposito, E., Grimminger, A., Hammer, B., Haeb-Umbach, R., Horwath, I., Hüllermeier, E., Kern, F., Kopp, S., Thommes, K., Ngonga Ngomo, A.-C., Schulte, C., Wachsmuth, H., Wagner, P., & Wrede, B. (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. https://doi.org/10.1109/tcds.2020.3044366
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Konferenzbeiträge
2024
Stratmann, L., Banh, N. C., Scharlau, I., & Dressler, F. (2024). Safety Assistance Systems for Bicyclists: Toward Empirical Studies of the Dooring Problem. ACM Symposium on Principles of Distributed Computing (PODC 2024), Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating Algorithms for Distributed Systems (ApPLIED 2024). https://doi.org/10.1145/3663338.3665831
Kolpaczki, P., Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. In S. Dasgupta, S. Mandt, & Y. Li (Eds.), Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (Vol. 238, pp. 3520–3528). PMLR.
Thommes, K., Lammert, O., Schütze, C., Richter, B., & Wrede, B. (2024). Human Emotions in AI Explanations. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-031-63803-9_15
Beierling, H., Loos, K., Helmert, R., & Vollmer, A.-L. (2024). Advancing Human-Robot Collaboration: The Impact of Flexible Input Mechanisms. Robotics: Science and Systems, Delf.
Sengupta, M., El Baff, R., Alshomary, M., & Wachsmuth, H. (2024). Analyzing the Use of Metaphors in News Editorials for Political Framing. In K. Duh, H. Gomez, & S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 3621–3631). Association for Computational Linguistics.
Alshomary, M., Lange, F., Booshehri, M., Sengupta, M., Cimiano, P., & Wachsmuth, H. (2024). Modeling the Quality of Dialogical Explanations. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 11523–11536). ELRA and ICCL.
Türk, O., Lazarov, S., Wang, Y., Buschmeier, H., Grimminger, A., & Wagner, P. (n.d.). Predictability of understanding in explanatory interactions based on multimodal cues. Proceedings of the 26th ACM International Conference on Multimodal Interaction. The 26th ACM International Conference on Multimodal Interaction, San José, Costa Rica. https://doi.org/10.1145/3678957.3685741
Wang, Y., Xu, Y., Skantze, G., & Buschmeier, H. (2024). How much does nonverbal communication conform to entropy rate constancy?: A case study on listener gaze in interaction. Findings of the Association for Computational Linguistics ACL 2024, 3533–3545.
Booshehri, M., Buschmeier, H., & Cimiano, P. (n.d.). A model of factors contributing to the success of dialogical explanations. Proceedings of the 26th ACM International Conference on Multimodal Interaction. 26th ACM International Conference on Multimodal Interaction, San José, Costa Rica. https://doi.org/10.1145/3678957.3685744
Battefeld, D., Mues, S., Wehner, T., House, P., Kellinghaus, C., Wellmer, J., & Kopp, S. (2024). Revealing the Dynamics of Medical Diagnostic Reasoning as Step-by-Step Cognitive Process Trajectories. Proceedings of the 46th Annual Conference of the Cognitive Science Society. The Annual Meeting of the Cognitive Science Society, Rotterdam, NL.
Wagner, P., Włodarczak, M., Buschmeier, H., Türk, O., & Gilmartin, E. (2024). Turn-taking dynamics across different phases of explanatory dialogues. Proceedings of the 28th Workshop on the Semantics and Pragmatics of Dialogue, 6–14.
Pilán, I., Prévot, L., Buschmeier, H., & Lison, P. (2024). Conversational feedback in scripted versus spontaneous dialogues: A comparative analysis. Proceedings of the 25th Meeting of the Special Interest Group on Discourse and Dialogue, 440–457. https://doi.org/10.18653/v1/2024.sigdial-1.38
Booshehri, M., Buschmeier, H., Cimiano, P., Kopp, S., Kornowicz, J., Lammert, O., Matarese, M., Mindlin, D., Robrecht, A. S., Vollmer, A.-L., Wagner, P., & Wrede, B. (2024). Towards a Computational Architecture for Co-Constructive Explainable Systems. Proceedings of the 2024 Workshop on Explainability Engineering, 20–25. https://doi.org/10.1145/3648505.3648509
Booshehri, M., Buschmeier, H., & Cimiano, P. (n.d.). Towards a BFO-based ontology of understanding in explanatory interactions. Proceedings of the 4th International Workshop on Data Meets Applied Ontologies in Explainable AI (DAO-XAI). 4th International Workshop on Data Meets Applied Ontologies in Explainable AI (DAO-XAI), Santiago de Compostela, Spain.
Riechmann, A. N., & Buschmeier, H. (2024). Automatic reconstruction of dialogue participants’ coordinating gaze behavior from multiple camera perspectives. Book of Abstracts of the 2nd International Multimodal Communication Symposium, 38–39.
Liedeker, F., Sanchez-Graillet, O., Seidler, M., Brandt, C., Wellmer, J., & Cimiano, P. (n.d.). A User Study Evaluating Argumentative Explanations in Diagnostic Decision Support. First Workshop on Natural Language Argument-Based Explanations, Santiago de Compostela, Spain.
Liedeker, F., Düsing, C., Nieveler, M., & Cimiano, P. (2024). An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet-Spot of Explanation Complexity. 2nd World Conference on eXplainable Artificial Intelligence, Valetta, Malta.
Battefeld, D., Liedeker, F., Cimiano, P., & Kopp, S. (2024). ASCODI: An XAI-based interactive reasoning support system for justifiable medical diagnosing. Proceedings of the 1st Workshop on Multimodal, Affective and Interactive EXplainable AI (MAI-XAI). European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, Spain.
Singh, A., & Rohlfing, K. J. (2024). Coupling of Task and Partner Model: Investigating the Intra-Individual Variability in Gaze during Human–Robot Explanatory Dialogue. Proceedings of 26th ACM International Conference on Multimodal Interaction (ICMI 2024). 26th ACM International Conference on Multimodal Interaction (ICMI 2024), San Jose, Costa Rica. https://doi.org/10.1145/3686215.3689202
2023
Rautenberg, F., Kuhlmann, M., Wiechmann, J., Seebauer, F., Wagner, P., & Haeb-Umbach, R. (2023). On Feature Importance and Interpretability of Speaker Representations. ITG Conference on Speech Communication. ITG Conference on Speech Communication, Aachen.
Wiechmann, J., Rautenberg, F., Wagner, P., & Haeb-Umbach, R. (2023). Explaining voice characteristics to novice voice practitioners-How successful is it? 20th International Congress of the Phonetic Sciences (ICPhS) .
Lebedeva, A., Kornowicz, J., Lammert, O., & Papenkordt, J. (2023). The Role of Response Time for Algorithm Aversion in Fast and Slow Thinking Tasks. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_9
Peters, T. M., & Visser, R. W. (2023). The Importance of Distrust in AI. Communications in Computer and Information Science. https://doi.org/10.1007/978-3-031-44070-0_15
Seebauer, F., Kuhlmann, M., Haeb-Umbach, R., & Wagner, P. (2023). Re-examining the quality dimensions of synthetic speech. 12th Speech Synthesis Workshop (SSW) 2023.
Terfloth, L., Schaffer, M., Buhl, H. M., & Schulte, C. (2023). Adding Why to What? Analyses of an Everyday Explanation. 1st World Conference on eXplainable Artificial Intelligence (xAI 2023), Lisboa. https://doi.org/10.1007/978-3-031-44070-0_13
Alpsancar, S. (2023). What is AI Ethics? Ethics as means of self-regulation and the need for critical reflection . International Conference on Computer Ethics 2023, 1(1), 1--17.
Robrecht, A., & Kopp, S. (2023). SNAPE: A Sequential Non-Stationary Decision Process Model for Adaptive Explanation Generation. Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 48–58. https://doi.org/10.5220/0011671300003393
Dyck, L., Beierling, H., Helmert, R., & Vollmer, A.-L. (2023). Technical Transparency for Robot Navigation Through AR Visualizations. Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, 720–724. https://doi.org/10.1145/3568294.3580181
Rautenberg, F., Kuhlmann, M., Ebbers, J., Wiechmann, J., Seebauer, F., Wagner, P., & Haeb-Umbach, R. (2023). Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics. Fortschritte Der Akustik - DAGA 2023, 1409–1412.
Hanselle, J., Kornowicz, J., Heid, S., Thommes, K., & Hüllermeier, E. (2023). Comparing Humans and Algorithms in Feature Ranking: A Case-Study in the Medical Domain. Lernen, Wissen, Daten, Analysen (LWDA) Conference Proceedings. Lernen, Wissen, Daten, Analysen 2023, Marburg, Germany.
Fumagalli, F., Muschalik, M., Hüllermeier, E., & Hammer, B. (2023). On Feature Removal for Explainability in Dynamic Environments. ESANN 2023 Proceedings. ESANN 2023 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges (Belgium) and online. https://doi.org/10.14428/esann/2023.es2023-148
Fumagalli, F., Muschalik, M., Kolpaczki, P., Hüllermeier, E., & Hammer, B. (2023). SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NeurIPS 2023 - Advances in Neural Information Processing Systems, 36, 11515--11551.
Sengupta, M., Alshomary, M., Scharlau, I., & Wachsmuth, H. (2023). Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. Findings of the Association for Computational Linguistics: EMNLP 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.308
Sengupta, M., Alshomary, M., & Wachsmuth, H. (2023). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 3rd Workshop on Figurative Language Processing (FLP). https://doi.org/10.18653/v1/2022.flp-1.19
Schütze, C., Lammert, O., Richter, B., Thommes, K., & Wrede, B. (2023). Emotional Debiasing Explanations for Decisions in HCI. Artificial Intelligence in HCI. https://doi.org/10.1007/978-3-031-35891-3_20
Robrecht, A., & Kopp, S. (2023). SNAPE: A Sequential Non-Stationary Decision Process Model for Adaptive Explanation Generation. Proceedings of the 15th International Conference on Agents and Artificial Intelligence. https://doi.org/10.5220/0011671300003393
Robrecht, A., Rothgänger, M., & Kopp, S. (2023). A Study on the Benefits and Drawbacks of Adaptivity in AI-generated Explanations. Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents. https://doi.org/10.1145/3570945.3607339
Fisher, J., Robrecht, A., Kopp, S., & Rohlfing, K. (2023). Exploring the Semantic Dialogue Patterns of Explanations – a Case Study of Game Explanations. Proceedings of the 27th Workshop on the Semantics and Pragmatics of Dialogue . Semdial, Maribor.
Sengupta, M., Alshomary, M., Scharlau, I., & Wachsmuth, H. (2023). Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In H. Bouamor, J. Pino, & K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 4636–4659). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.308
Beer, F., & Schulz, C. (n.d.). The Return of Black Box Theory in Explainable AI. 4S Conference (Society for the Social Studies of Science), Honolulu/Hawaii, November 9.
Wang, Y., & Buschmeier, H. (2023). Does listener gaze in face-to-face interaction follow the Entropy Rate Constancy principle: An empirical study. Findings of the Association for Computational Linguistics: EMNLP 2023, 15372–15379.
Singh, A., & Rohlfing, K. J. (2023). Contrastiveness in the context of action demonstration: an eye-tracking study on its effects on action perception and action recall. Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45). 45th Annual Conference of the Cognitive Science Society, Sydney.
Liedeker, F., & Cimiano, P. (2023). A Prototype of an Interactive Clinical Decision Support System with Counterfactual Explanations. xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lissabon.
2022
Wiechmann, J., Glarner, T., Rautenberg, F., Wagner, P., & Haeb-Umbach, R. (2022). Technically enabled explaining of voice characteristics. 18. Phonetik Und Phonologie Im Deutschsprachigen Raum (P&P).
Groß, A., Schütze, C., Wrede, B., & Richter, B. (2022). An Architecture Supporting Configurable Autonomous Multimodal Joint-Attention-Therapy for Various Robotic Systems. INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 154–159. https://doi.org/10.1145/3536220.3558070
Schütze, C., Groß, A., Wrede, B., & Richter, B. (2022). Enabling Non-Technical Domain Experts to Create Robot-Assisted Therapeutic Scenarios via Visual Programming. INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 166–170. https://doi.org/10.1145/3536220.3558072
Sieger, L. N., Hermann, J., Schomäcker, A., Heindorf, S., Meske, C., Hey, C.-C., & Doğangün, A. (2022). User Involvement in Training Smart Home Agents. International Conference on Human-Agent Interaction. HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand. https://doi.org/10.1145/3527188.3561914
Finke, J., Horwath, I., Matzner, T., & Schulz, C. (2022). (De)Coding social practice in the field of XAI: Towards a co-constructive framework of explanations and understanding between lay users and algorithmic systems. Artificial Intelligence in HCI, 149–160. https://doi.org/10.1007/978-3-031-05643-7_10
Wachsmuth, H., & Alshomary, M. (2022). “Mama Always Had a Way of Explaining Things So I Could Understand”: A Dialogue Corpus for Learning to Construct Explanations. In N. Calzolari, C.-R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K.-S. Choi, P.-M. Ryu, H.-H. Chen, L. Donatelli, H. Ji, S. Kurohashi, P. Paggio, N. Xue, S. Kim, Y. Hahm, Z. He, T. K. Lee, E. Santus, F. Bond, & S.-H. Na (Eds.), Proceedings of the 29th International Conference on Computational Linguistics (pp. 344–354). International Committee on Computational Linguistics.
Sengupta, M., Alshomary, M., & Wachsmuth, H. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 2022 Workshop on Figurative Language Processing.
Finke, J., Horwath, I., Matzner, T., & Schulz, C. (2022). (De)Coding Social Practice in the Field of XAI: Towards a Co-constructive Framework of Explanations and Understanding Between Lay Users and Algorithmic Systems. Artificial Intelligence in HCI, 149–160. https://doi.org/10.1007/978-3-031-05643-7_10
Battefeld, D., & Kopp, S. (2022). Formalizing cognitive biases in medical diagnostic reasoning. Proceedings of the 8th Workshop on Formal and Cognitive Reasoning. 8th Workshop on Formal and Cognitive Reasoning (FCR), Trier.
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Konferenz Abstracts
2024
Banh, N. C., & Scharlau, I. (2024). Effects of task difficulty on visual processing speed. Tagung experimentell arbeitender Psycholog:innen (TeaP), Regensburg.
Alpsancar, S., Matzner, T., & Philippi, M. (2024). Unpacking the purposes of explainable AI. Smart Ethics in the Digital World: Proceedings of the ETHICOMP 2024. 21th International Conference on the Ethical and Social Impacts of ICT, 31–35.
2023
Banh, N. C., & Scharlau, I. (2023). First steps towards real-time assessment of attentional weights and capacity according to TVA. In S. Merz, C. Frings, B. Leuchtenberg, B. Moeller, S. Mueller, R. Neumann, B. Pastötter, L. Pingen, & G. Schui (Eds.), Abstracts of the 65th TeaP. ZPID (Leibniz Institute for Psychology). https://doi.org/10.23668/PSYCHARCHIVES.12945
Liedeker, F., & Cimiano, P. (2023). Dynamic Feature Selection in AI-based Diagnostic Decision Support for Epilepsy. 1st International Conference on Artificial Intelligence in Epilepsy and Neurological Disorders, Breckenridge, CO, USA .
2022
Banh, N. C., & Scharlau, I. (2022). Effects of verbal negation on TVA’s capacity and weight parameters. In S. Malejka, M. Barth, H. Haider, & C. Stahl (Eds.), TeaP 2022 - Abstracts of the 64th Conference of Experimental Psychologists . Pabst Science Publishers. https://doi.org/10.23668/psycharchives.5677
Banh, N. C., Scharlau, I., & Rohlfing, K. J. (2022). Folgen wiederholter Negation auf die Aufmerksamkeit. In C. Bermeitinger & W. Greve (Eds.), 52. Kongress der Deutschen Gesellschaft für Psychologie.
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