Pius von Däniken

Projekte

• Unified Model for Evaluation of Text Generation Systems / Teammitglied / laufend
• Social Influencer:in / Teammitglied / laufend
• Holistic Analysis of Organised Misinformation Activity in Social Networks / Teammitglied / abgeschlossen
• PRISM: Predicting Radicalization Events in Social Media User Timelines / Teammitglied / abgeschlossen
• Verbreitung von Fake News und Hate Speech auf Social Media in der Schweiz / Projektleiter:in / abgeschlossen
• DOSSMA – Erkennung von verdächtigem Verhalten in Social Media / Teammitglied / abgeschlossen
• SCAI – Smart Contract Analytics using Artificial Intelligence / Teammitglied / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

• Schreiber, M., Jenny, G. J., Hürlimann, M., Parfenova, Y., von Däniken, P., & Cieliebak, M. (2025). A discourse on the use of machine learning (ML) in personality psychology : can we expect ML to predict questionnaire scores from idiographic text-based data? Journal of Research in Personality, 119(104666). https://doi.org/10.1016/j.jrp.2025.104666
• Tuggener, L., Amirian, M., Benites de Azevedo e Souza, F., von Däniken, P., Gupta, P., Schilling, F.-P., & Stadelmann, T. (2020). Design patterns for resource-constrained automated deep-learning methods. Ai, 1(4), 510–538. https://doi.org/10.3390/ai1040031

Schriftliche Konferenzbeiträge, peer-reviewed

• Giedemann, P., von Däniken, P., Deriu, J. M., Rodrigo, A., Peñas, A., & Cieliebak, M. (2025). ViClaim : a multilingual multilabel dataset for automatic claim detection in videos [Conference paper]. In C. Christodoulopoulos, T. Chakraborty, C. Rose, & V. Peng (Eds.), Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (pp. 397–413). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-main.21
• Schmid, L., von Däniken, P., Giedemann, P., Tuggener, D., Bühler, J., Kamenowski, M., Girschik, K., Baier, D., & Cieliebak, M. (2025). HICC : a dataset for German hate speech in conversational context [Conference paper]. Proceedings of the 21st Conference on Natural Language Processing (KONVENS 2025), 168–176. https://doi.org/10.21256/zhaw-35860
• von Däniken, P., Deriu, J. M., & Cieliebak, M. (2025). A measure of the system dependence of automated metrics [Conference paper]. In W. Che, J. Nabende, E. Shutova, & M. T. Pilehvar (Eds.), Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 87–99). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.acl-short.8
• Tuggener, D., Schneider, T., Huwiler, A., Kreienbühl, T., Hischier, S., von Däniken, P., & Niehaus, S. (2024). Role-playing LLMs in professional communication training : the case of investigative interviews with children [Conference paper]. In P. H. Luz de Araujo, A. Baumann, D. Gromann, B. Krenn, B. Roth, & M. Wiegand (Eds.), Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024) (pp. 249–263). Association for Computational Linguistics. https://doi.org/10.21256/zhaw-31482
• von Däniken, P., Deriu, J. M., Tuggener, D., & Cieliebak, M. (2024). Favi-Score : a measure for favoritism in automated preference ratings for generative AI evaluation [Conference paper]. In L.-W. Ku, A. Martins, & V. Srikumar (eds.), Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 4437–4454). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.acl-long.243
• von Däniken, P., Deriu, J. M., Rodrigo, A., & Cieliebak, M. (2024). Improving quantification with minimal in-domain annotations : beyond classify and count [Conference paper]. Proceedings of the International AAAI Conference on Web and Social Media, 18(1), 1585–1598. https://doi.org/10.1609/icwsm.v18i1.31411
• Deriu, J., von Däniken, P., Tuggener, D., & Cieliebak, M. (2023). Correction of errors in preference ratings from automated metrics for text generation [Conference paper]. In A. Rogers, R. Boyd-Graber, & N. Okazaki (Eds.), Findings of the Association for Computational Linguistics: ACL 2023 (pp. 6456–6474). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-acl.404
• von Däniken, P., Deriu, J. M., & Cieliebak, M. (2023). ZHAW-CAI at CheckThat! 2023 : ensembling using kernel averaging [Conference paper]. In M. Aliannejadi, G. Faggioli, N. Ferro, & M. Vlachos (Eds.), Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023) (pp. 534–545). CEUR Workshop Proceedings. https://doi.org/10.21256/zhaw-29046
• von Däniken, P., Deriu, J. M., Agirre, E., Brunner, U., Cieliebak, M., & Stockinger, K. (2022). Improving NL-to-Query systems through re-ranking of semantic hypothesis [Conference paper]. In M. Abbas & A. A. Freihat (Eds.), Proceedings of the 5th International Conference on Natural Language and Speech Processing (ICNLSP 2022) (pp. 57–67). Association for Computational Linguistics. https://doi.org/10.21256/zhaw-26147
• Deriu, J. M., Tuggener, D., von Däniken, P., & Cieliebak, M. (2022). Probing the robustness of trained metrics for conversational dialogue systems [Conference paper]. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2, 750–761. https://doi.org/10.18653/v1/2022.acl-short.85
• Benites de Azevedo e Souza, F., Hürlimann, M., von Däniken, P., & Cieliebak, M. (2020). ZHAW-InIT : social media geolocation at VarDial 2020 [Conference paper]. In M. Zampieri, P. Nakov, N. Ljubešić, J. Tiedemann, & Y. Scherrer (Eds.), Proceedings of the 7th Workshop on NLP for Similar Languages, Varieties and Dialects (pp. 254–264). International Committee on Computational Linguistics (ICCL). https://doi.org/10.21256/zhaw-21551
• Deriu, J. M., Tuggener, D., von Däniken, P., Campos, J. A., Rodrigo, A., Belkacem, T., Soroa, A., Agirre, E., & Cieliebak, M. (2020). Spot The Bot : a robust and efficient framework for the evaluation of conversational dialogue systems [Conference paper]. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 3971–3984. https://doi.org/10.18653/v1/2020.emnlp-main.326
• Büchi, M., Ulasik, M. A., Hürlimann, M., Benites de Azevedo e Souza, F., von Däniken, P., & Cieliebak, M. (2020). ZHAW-InIT at GermEval 2020 task 4 : low-resource speech-to-text [Conference paper]. In S. Ebling, D. Tuggener, M. Hürlimann, M. Cieliebak, & M. Volk (Eds.), Proceedings of the 5th Swiss Text Analytics Conference (SwissText) & 16th Conference on Natural Language Processing (KONVENS). CEUR Workshop Proceedings. https://doi.org/10.21256/zhaw-21550
• Benites de Azevedo e Souza, F., Duivesteijn, G. F., von Däniken, P., & Cieliebak, M. (2020). TRANSLIT : a large-scale name transliteration resource [Conference paper]. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), 3265–3271. https://doi.org/10.21256/zhaw-20082
• Tuggener, D., von Däniken, P., Peetz, T., & Cieliebak, M. (2020). LEDGAR : a large-scale multi-label corpus for text classification of legal provisions in contracts [Conference paper]. Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), 1235–1241. https://doi.org/10.21256/zhaw-20087
• Benites de Azevedo e Souza, F., von Däniken, P., & Cieliebak, M. (2019). TwistBytes - identification of Cuneiform languages and German dialects at VarDial 2019 [Conference paper]. Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, 194–201. https://doi.org/10.18653/v1/W19-1421
• Benites de Azevedo e Souza, F., Duivesteijn, G., von Däniken, P., & Cieliebak, M. (2018). Merging haystacks to find matching needles : a transliteration approach. SwissText 2018: 3rd Swiss Text Analytics Conference, Winterthur, 12.-13. Juni 2018.
• von Däniken, P., Grubenmann, R., & Cieliebak, M. (2018). Word unigram weighing for author profiling at PAN 2018 : notebook for PAN at CLEF 2018 [Conference poster]. CLEF 2018 Evaluation Labs and Workshop – Working Notes Papers (PAN), 2125. http://ceur-ws.org/Vol-2125/paper_135.pdf
• von Grünigen, D., Grubenmann, R., Benites de Azevedo e Souza, F., von Däniken, P., & Cieliebak, M. (2018). spMMMP at GermEval 2018 shared task : classification of offensive content in tweets using convolutional neural networks and gated recurrent units [Conference paper]. Proceedings of the GermEval 2018 Workshop : 14th Conference on Natural Language Processing - KONVENS 2018, 130–137. https://www.oeaw.ac.at/fileadmin/subsites/academiaecorpora/PDF/GermEval2018_Proceedings.pdf
• Benites de Azevedo e Souza, F., Grubenmann, R., von Däniken, P., von Grünigen, D., Deriu, J. M., & Cieliebak, M. (2018). Twist Bytes : German dialect identification with data mining optimization [Conference paper]. Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018), 218–227. https://doi.org/10.21256/zhaw-4850
• Grubenmann, R., Tuggener, D., von Däniken, P., Deriu, J. M., & Cieliebak, M. (2018). SB-CH : a Swiss German corpus with sentiment annotations. Proceedings of the Eleventh International Conference on Language Resources and Evaluation, LREC 2018.
• Graf, H. D., Koc, Y., Panighetti, S., Togni, M., von Grünigen, D., Weilenmann, M., Xhoxhaj, E., Zürrer, D., Benites de Azevedo e Souza, F., Deriu, J. M., Neureiter, N., von Däniken, P., Cieliebak, M., Eich, W., Neuhaus, S., & Stockinger, K. (2017). Four different ways to build a chatbot about movies. SwissText 2017: 2nd Swiss Text Analytics Conference, Winterthur, 9. Juni 2017.

Weitere Publikationen

• Bühler, J., Jetzer, K., Seiwald, J., von Däniken, P., Kamenowski, M., Girschik, K., Baier, D., Sedano, L., Schmid, L., Tuggener, D., & Giedemann, P. (2026). Social Influencer:in: mit wirksamer Gesprächsführung gegen Hass im Netz. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-36018
• Bühler, J., von Däniken, P., Girschik, K., Giedemann, P., Kamenowski, M., Tuggener, D., & Baier, D. (2025). Social Influencer:in: mit wirksamer Gesprächsführung gegen Hass im Netz : Bericht 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-32956
• von Däniken, P., Deriu, J. M., Tuggener, D., & Cieliebak, M. (2022). On the effectiveness of automated metrics for text generation systems [Conference paper]. Findings of the Association for Computational Linguistics: EMNLP 2022, 1503–1522. https://doi.org/10.21256/zhaw-27042
• von Däniken, P. (2021). Improving a semantic parser through user interaction. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-22938
• von Däniken, P., Hürlimann, M., & Cieliebak, M. (2020). Overview of the GermEval 2020 shared task on Swiss German language identification [Conference paper]. In S. Ebling, D. Tuggener, M. Hürlimann, M. Cieliebak, & M. Volk (Eds.), Proceedings of the 5th Swiss Text Analytics Conference (SwissText) & 16th Conference on Natural Language Processing (KONVENS). CEUR Workshop Proceedings. https://doi.org/10.21256/zhaw-21549

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