Publikationen
245 Übereinstimmungen gefunden / 1-15 16-30 31-45 46-60 61-75 76-90 91-105 106-120 121-135 136-150 151-165 166-180 181-195 196-210 211-225 226-240 241-245
Datenschutzrechtliche Anforderungen bei Online-Umfragen.Buck, D., Herrenbrück, R., Jacob, K., Lukowski, F., Schneider, J., Thaut, A., & Verbund Forschungsdaten Bildung (2025).Datenschutzrechtliche Anforderungen bei Online-Umfragen. Frankfurt/Main: DIPF, Leibniz-Institut für Bildungsforschung und Bildungsinformation. https://doi.org/10.25656/01:33518 |
AutoML meets hugging face: Domain-aware pretrained model selection for text classification.Safikhani, P., & Broneske, D. (2025).AutoML meets hugging face: Domain-aware pretrained model selection for text classification. In A. Ebrahimi, S. Haider, E. Liu, M. L. Pacheco, & S. Wein (Hrsg.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop). Albuquerque, USA: Association for Computational Linguistics. Abstract
The effectiveness of embedding methods is crucial for optimizing text classification performance in Automated Machine Learning (AutoML). However, selecting the most suitable pre-trained model for a given task remains challenging. This study introduces the Corpus-Driven Domain Mapping (CDDM) pipeline, which utilizes a domain-annotated corpus of pre-fine-tuned models from the Hugging Face Model Hub to improve model selection. Integrating these models into AutoML systems significantly boosts classification performance across multiple datasets compared to baseline methods. Despite some domain recognition inaccuracies, results demonstrate CDDM’s potential to enhance model selection, streamline AutoML workflows, and reduce computational costs. |
NVM in data storage: A post-optane future.Karim, S., Wünsche, J., Kuhn, M., Saake, G., & Broneske, D. (2025).NVM in data storage: A post-optane future. ACM Digital Library, ACM Transaction on Storage21(3). https://doi.org/10.1145/3731454 (Abgerufen am: 01.07.2025). https://doi.org/10.1145/3731454 |
Following political science students through their methods training: Statistics anxiety, student satisfaction, and final grades in the COVID year 2021/22.Vierus, P., Elis, J., Ziller, C., Goerres, A., & Höhne, J. K. (2025).Following political science students through their methods training: Statistics anxiety, student satisfaction, and final grades in the COVID year 2021/22. Politische Vierteljahresschrift (online first). https://doi.org/10.1007/s11615-025-00613-x |
VerbCraft: Morphologically-aware Armenian text generation using LLMs in low-resource settings.Avetisyan, H., & Broneske, D. (2025).VerbCraft: Morphologically-aware Armenian text generation using LLMs in low-resource settings. In ¦. A. Holdt, N. Ilinykh, B. Scalvini, M. Bruton, I. N. Debess, & C. M. Tudor (Hrsg.), Proceedings of the Third Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2025) (S. 111-119). Tallinn: University of Tartu Library, Estonia. |
Trendumfrage Forschungsdateninfrastrukturen 2024.Hartstein, J., Blümel, C., & Klein, D. (2025).Trendumfrage Forschungsdateninfrastrukturen 2024. Daten- und Methodenbericht. Hannover: DZHW. Abstract
Die Trendumfrage Forschungsdateninfrastrukturen 2024 (Umfrage FDI 2024) ist Teil der Begleitforschung zu den Nationalen Forschungsdateninfrastruktur (NFDI)-Basisdiensten (Base4NFDI). Die Umfrage FDI 2024 erfasst die Wahrnehmung, Nutzung und Bewertung bestehender und neuer Dateninfrastrukturen und Dienste in der deutschen Forschungslandschaft. Der Fokus liegt auf der Perspektive der (potenziellen) Nutzenden. |
Stata tip 160: Drop capture program drop from ado-files.Klein, D. (2025).Stata tip 160: Drop capture program drop from ado-files. The Stata Journal, 2025(1), 252-253. https://doi.org/10.1177/1536867X251322974 Abstract
I explain that -capture program drop- is useless in ado-files. While it prevents errors in do-files when redefining programs in memory, it either isn't executed or results in an error in ado-files. Moreover, in ado-files with local subroutines, -capture program drop- can mistakenly remove unrelated programs from memory. |
Tell me more! Using multiple features for binary text classification with a zero-shot model.Broneske, D., Italiya, N., & Mierisch, F. (2025).Tell me more! Using multiple features for binary text classification with a zero-shot model. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), 2024 International Conference on Machine Learning and Applications (ICMLA) (S. 1613-1620). Jacksonville, Florida, USA: IEEE Xplore. https://doi.org/10.1109/ICMLA61862.2024.00249 |
Effective and transparent attributions for fake news classification and search.Thiel, M., Shahania, S., & Nürnberger, A. (2025).Effective and transparent attributions for fake news classification and search. In F. Naretto & R. Pellungrini (Hrsg.), Proceedings of the Discovery Science Late Breaking Contributions 2024 (DS-LB 2024). Aachen: Ceur Workshop Proceedings. |
The standardized data management plan for educational research, an approach to foster tailored data management.Netscher, S., Kaluza, H., Mauer, R., Mozygemba, K., & Stephan, K. (2025).The standardized data management plan for educational research, an approach to foster tailored data management. International Journal of Digital Curation, 2025(1). https://doi.org/10.2218/ijdc.v19i1.910 |
ADAMANT: Hardware-accelerated query processing made easy.Broneske, D., Burtsev, V., Drewes, A., Gurumurthy, B., Pionteck, T., & Saake, G. (2025).ADAMANT: Hardware-accelerated query processing made easy. In K.-U. Sattler, A. Kemper, T. Neumann, & J. Teubner (Hrsg.), Scalable Data Management for Future Hardware (S. 1-38). Cham: Springer. https://doi.org/10.1007/978-3-031-74097-8 |
DZHW Scientists Survey 2023. Data and methods report on the DZHW Scientists Survey 2023.Fabian, G., Heger, C., Just, A., Weber, A., & Oestreich, T. (2025).DZHW Scientists Survey 2023. Data and methods report on the DZHW Scientists Survey 2023. Hannover: DZHW. https://doi.org/10.21249/DZHW:scs2023-dmr-en:1.0.1 Abstract
The DZHW Scientists Survey 2023 is an online survey of full-time academic and artistic staff at German universities and equivalent institutions of higher education with the right to award doctorates. It is repeated at regular intervals as a trend study to explore the working and research conditions at German universities and equivalent institutions of higher education. The DZHW Scientists Survey 2023 was conducted from January to March 2023. The respondents therefore take a retrospective look at their working and research conditions during the Covid-19 pandemic and their current post-pandemic situation. The previous Scientists Surveys took place in 2010, 2016 and 2019/2020. [...] Full Abstract: https://doi.org/10.21249/DZHW:scs2023:1.0.1 |
DZHW-Wissenschaftsbefragung 2023.Fabian, G., Heger, C., Just, A., & Weber, A. (2025).DZHW-Wissenschaftsbefragung 2023. Daten- und Methodenbericht zur DZHW-Wissenschaftsbefragung 2023. Hannover: DZHW. https://doi.org/10.21249/DZHW:scs2023-dmr-de:1.0.1 Abstract
Die DZHW-Wissenschaftsbefragung 2023 ist eine Onlinebefragung des hauptberuflichen wissenschaftlich-künstlerischen Personals an deutschen Universitäten und gleichgestellten Hochschulen mit Promotionsrecht. Sie wird als Trendstudie zur Erforschung der Arbeits- und Forschungsbedingungen an deutschen Universitäten und gleichgestellten Hochschulen in regelmäßigen Abständen wiederholt. Die DZHW-Wissenschaftsbefragung 2023 wurde von Januar bis März 2023 durchgeführt. Die Befragten blicken also retrospektiv auf ihre Arbeits- und Forschungsbedingungen während der Covid-19-Pandemie sowie auf ihre aktuelle postpandemische Situation. [...] Vollständiger Abstract: https://doi.org/10.21249/DZHW:scs2023:1.0.1 |
Explaining item-nonresponse in open questions with requests for voice responses.Salvatore, C., & Höhne, J. K. (2025).Explaining item-nonresponse in open questions with requests for voice responses. In A. Pollice & P. Mariani (Hrsg.), Methodological and Applied Statistics and Demography IV (S. 483-489). Cham: Springer. https://doi.org/10.1007/978-3-031-64447-4_82 |
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