Dr. Jonathan Fürst

Netzwerk

Mitglied in Netzwerken

• Linkedin
• Google Scholar
• Github
• Website

Projekte

• Watt Counts: Auf dem Weg zu energieeffizienter Inferenz von Large Language Models / Projektleiter:in / laufend
• DataGEMS - Data Discovery Platform with Generalized Exploratory, Management, and Search Capabilities (Horizon Europe) / Teammitglied / laufend
• Digital Health Zurich: ein Praxislabor für patientenzentrierte klinische Innovation / Teammitglied / laufend
• Schluss mit Multiple Choice! / Projektleiter:in / abgeschlossen
• KI gestütztes Qualitätsmanagement von BIM-Modellen / Projektleiter:in / abgeschlossen
• Reliable Multi-lingual and Cross-lingual Open Data Exploration in Natural Language / Teammitglied / abgeschlossen

Publikationen

Schriftliche Konferenzbeiträge, peer-reviewed

• Colakoglu, G., Solmaz, G., & Fürst, J. (2025). Problem solved? Information extraction design space for layout-rich documents using LLMs [Conference paper]. Findings of the Association for Computational Linguistics: EMNLP 2025, 17908–17927. https://doi.org/10.18653/v1/2025.findings-emnlp.973
• Nooralahzadeh, F., Zhang, Y., Fürst, J., & Stockinger, K. (2025). Multi-modal data exploration via language agents [Conference paper]. In K. Inui, S. Sakti, H. Wang, D. F. Wong, P. Bhattacharyya, B. Banerjee, A. Ekbal, T. Chakraborty, & D. P. Singh (Eds.), Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (pp. 795–813). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.findings-ijcnlp.47
• Stuhlmann, L., Saxer, M. A., & Fürst, J. (2025). Efficient and reproducible biomedical question answering using retrieval augmented generation [Conference paper]. 154–157. https://doi.org/10.1109/sds66131.2025.00029
• Fürst, J., Kosten, C., Nooralahzadeh, F., Zhang, Y., & Stockinger, K. (2025). Evaluating the data model robustness of Text-to-SQL systems based on real user queries [Conference paper]. Proceedings of EDBT 2025, 158–170. https://doi.org/10.48786/edbt.2025.13
• Sivasubramaniam, S., Osei-Akoto, C., Zhang, Y., Stockinger, K., & Fürst, J. (2024, December 12). SM3-Text-to-Query : synthetic multi-model medical text-to-query benchmark. 38th Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 10-15 December 2024. https://doi.org/10.21256/zhaw-32078
• Meyer, G., Breuer, P., & Fürst, J. (2024). ASAG2024 : a combined benchmark for short answer grading [Conference poster]. In M. Dorodchi (Ed.), SIGCSE Virtual 2024: Proceedings of the 2024 on ACM Virtual Global Computing Education Conference V. 2 (Vol. 2). Association for Computing Machinery. https://doi.org/10.1145/3649409.3691083
• Fürst, J., Fadel Argerich, M., & Cheng, B. (2023). VersaMatch : ontology matching with weak supervision [Conference paper]. In G. Koutrika & J. Yang (Eds.), Proceedings of the VLDB Endowment (Vol. 16, Issue 6, pp. 1305–1318). Association for Computing Machinery. https://doi.org/10.14778/3583140.3583148
• Garrido-Hidalgo, C., Fürst, J., Roda-Sanchez, L., Olivares, T., & Fernández-Caballero, A. (2023). Lessons learned on the design of a predictive agent for LoRaWAN network planning [Conference paper]. Advances in Practical Applications of Agents, Multi-Agent Systems, and Cognitive Mimetics : The PAAMS Collection, 13955. https://doi.org/10.1007/978-3-031-37616-0_8
• Solmaz, G., Cirillo, F., Fürst, J., Jacobs, T., Bauer, M., Kovacs, E., Santana, J. R., & Sánchez, L. (2022). Enabling data spaces : existing developments and challenges [Conference paper]. Proceedings of the 1st International Workshop on Data Economy, 42–48. https://doi.org/10.1145/3565011.3569058

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