Verfassungsmäßigkeit der Verlustverrechnungsbeschränkung für Termingeschäfte
Demmler, Uwe (2024)
Steuerrecht aktuell 2024 (2), 43-47.
Zum wirtschaftlich einheitlichen Erwerb nach § 8b Abs. 4 Satz 6 KStG
Demmler, Uwe (2024)
Steuerrecht aktuell 2024 (2), 51-54.
Gleichzeitige Zahlung von Geschäftsführergehalt und Pension
Demmler, Uwe (2024)
Steuerrecht aktuell 2024 (2), 50-51.
Forscher entwickeln Textscanner, um mit KI Manipulationen zu erkennen
Tominski, Katrin (2024)
Pensionskassen
Demmler, Uwe (2024)
Steuerrecht der betrieblichen Altersversorgung mit arbeitsrechtlicher Grundlegung Lfg. 53 / Juni 2024 / Band II / Teil 5, 71-168.
Second Workshop on AI for AI Education (AI4AILearning)
Kohlhase, Michael; Leidner, Jochen L.; Schmid, Ute; Wolter, Diedrich (2024)
held at KI 2024: 47. Deutsche Jahrestagung für Künstliche Intelligenz, Würzburg, 23.09. - 27.09.2024.
Peer Reviewed
Multidimensional AI-based Health-Assistant
Blümlein, Markus; Leidner, Jochen L. (2024)
Poster, presented at Networking for Research – German Universities of Applied Sciences and Researchers from Scotland (UDIF-HAW), DFG (German Research Foundation) and SULSA (Scottish Universities Life Sciences Alliances), online, 2024-04-24.
TAME II: A Modern Geographic Text Annotation Tool
Leidner, Jochen L.; Jung, Luca (2024)
Proceedings of the 21st International Symposium on Web and Wireless Geographical Information Systems (W2GIS 2024), June, 17-18, 2024, Yverdon-les-Bains, Switzerland
, 95-104.
DOI: 10.1007/978-3-031-60796-7_7
Peer Reviewed
Experiments in News Bias Detection with Pre-Trained Neural Transformers
Menzner, T.; Leidner, Jochen L. (2024)
Proceedings of the 29th European Conference on Information Retrieval (ECIR 2024), Glasgow, Scotland, UK, March 24-28, 2024 IV, 270-284.
DOI: 10.1007/978-3-031-56066-8_22
Peer Reviewed
Homo Narrans: From Information to Narratives
Leidner, Jochen L. (2024)
Invited Keynote, Seventh International Workshop on Narrative Extraction from Texts (Text2Story 2024) held in conjunction with the 46th European Conference on Information Retrieval (ECIR 2024), Glasgow, Scotland, UK, 23 March 2024.
Control in Hybrid Chatbots
Rüdel, Thomas; Leidner, Jochen L. (2023)
Technical Report, ArXiv Pre-Print Server.
DOI: 10.48550/arXiv.2311.11701
Open Access
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part I
Nowaczyk, Slawomir; Biecek, Przemyslaw; Chung, Neo Christopher; Vallati, Mauro; Skruch, Pawel; Jaworek-Korjakowska, Joanna; Parkinson, Simon; Nikitas, Alexandros; Atzmüller, Martin; Tomás, Kliegr; Schmid, Ute; Bobek, Szymon; Lavrac, Nada; Peeters, Marieke; van Dierendonck, Roland; Robben, Saskia; Mercier-Laurent, Eunika; Kayakutlu, Gülgün; Owoc, Mieczyslaw Lech; Mason, Karl; Wahid, Abdul; Bruno, Pierangela; Calimeri, Francesco; Cauteruccio, Francesco; Terracina, Giorgio; Wolter, Diedrich; Leidner, Jochen L.; Kohlhase, Michael; Dimitrova, Vania (2023)
Nowaczyk, Slawomir; Biecek, Przemyslaw; Chung, Neo Christopher; Vallati, Mauro...
Communications in Computer and Information Science (CCIS) 1947.
Peer Reviewed
Language-Model Assisted Learning How to Program?
Leidner, Jochen L.; Reiche, Michael (2023)
Workshop on AI for AI Learning Held at ECAI 2023, Kakow, Poland, September 30, 2023.
Peer Reviewed
Bridging the Programming Skill Gap with ChatGPT: A Machine Learning Project with Business Students
Reiche, Michael; Leidner, Jochen L. (2023)
Workshop on AI for AI Learning Held at ECAI 2023, Kakow, Poland, September 30, 2023.
Peer Reviewed
Topic Segmentation of Educational Video Lectures Using Audio and Text
Dimitsas, Markos; Leidner, Jochen L. (2023)
Workshop on AI for AI Learning Held at ECAI 2023, Kakow, Poland, September 30, 2023.
Peer Reviewed
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part II
Nowaczyk, Slawomir; Biecek, Przemyslaw; Chung, Neo Christopher; Vallati, Mauro; Skruch, Pawel; Jaworek-Korjakowska, Joanna; Parkinson, Simon; Nikitas, Alexandros; Atzmüller, Martin; Tomás, Kliegr; Schmid, Ute; Bobek, Szymon; Lavrac, Nada; Peeters, Marieke; van Dierendonck, Roland; Robben, Saskia; Mercier-Laurent, Eunika; Kayakutlu, Gülgün; Owoc, Mieczyslaw Lech; Mason, Karl; Wahid, Abdul; Bruno, Pierangela; Calimeri, Francesco; Cauteruccio, Francesco; Terracina, Giorgio; Wolter, Diedrich; Leidner, Jochen L.; Kohlhase, Michael; Dimitrova, Vania (2023)
Nowaczyk, Slawomir; Biecek, Przemyslaw; Chung, Neo Christopher; Vallati, Mauro...
Communications in Computer and Information Science (CCIS) 1948.
DOI: 10.1007/978-3-031-56066-8_22
Peer Reviewed
Digitalization of Controlling in Insurance Companies. Along the Limits of Insurability
Kraft, Mirko; Drerup, Bianca (2023)
in: Keimer, Imke; Egle, Ulrich (Hg.) (2023): The Digitalization of Management Accounting. Use Cases form Theory and Practice. Wiesbaden: Springer 2023, 277–293.
DOI: 10.1007/978-3-658-41524-2
This article deals with the digitalization of management accounting / controlling in insurance companies, which goes hand in hand with the digital transformation of the insurance industry by Big Data, Artificial Intelligence (AI) and Blockchain. The insurance business requires an industry-specific design of the controlling instruments, but not of the controlling concept itself. Managing insurance as a service in a value- and risk-oriented way requires cost transparency, e.g. through contribution margin calculations. Risks, on the other hand, can only be understood from a balance sheet perspective, e.g. through internal models. These interdisciplinary fields of application of controlling are undergoing digitalization. In addition, there are new market developments such as telematics tariffs, in which the digitalization of controlling is essential in order to address the limits of insurability. The fields of application result in new competence profiles of controllers in distinction to actuaries and data scientists.
Extractive Summarization of Financial Earnings Call Transcripts
Nugent, Timothy; Leidner, Jochen L.; Gkotsis, George (2023)
Advances in Information Retrieval: Proceedings of the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2-6, 2023 2, 3-15.
DOI: 10.1007/978-3-031-28238-6_1
Peer Reviewed
To date, automatic summarization methods have been mostly developed for (and applied to) general news articles, whereas other document types have been neglected. In this paper, we introduce the task of summarizing financial earnings call transcripts, and we present a method for summarizing this text type essential for the financial industry. Earnings calls are briefing events common for public companies in many countries, typically in the form of conference calls held between company executives and analysts that consist of a spoken monologue part followed by moderated questions and answers.
We show that traditional methods work less well in this domain, we present a method suitable for summarizing earnings calls. Our large-scale evaluation on a new human-annotated corpus of summary-worthy sentences shows that this method outperforms a set of strong baselines, including a new one that we propose specifically for earnings calls. To the best of our knowledge, this is the first application of summarization to financial earnings calls transcripts, a primary source of information for financial professionals.
Which Country Is This? Automatic Country Ranking of Street View Photos
Menzner, T.; Mittag, Florian; Leidner, Jochen L. (2023)
Advances in Information Retrieval: Proceedings of the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2-6, 2023 3, 275–280.
DOI: 10.1007/978-3-031-28241-6_26
Peer Reviewed
In this demonstration, we present Country Guesser, a live system that guesses the country that a photo is taken in. In particular, given a Google Street View image, our federated ranking model uses a combination of computer vision, machine learning and text retrieval methods to compute a ranking of likely countries of the location shown in a given image from Street View. Interestingly, using text-based features to probe large pre-trained language models can assist to provide cross-modal supervision. We are not aware of previous country guessing systems informed by visual and textual features.
Erklärbare Künstliche Intelligenz am Beispiel von Ratings deutscher Lebensversicherungsunternehmen
Bartel, Holger; Kraft, Mirko; Leidner, Jochen L. (2023)
Zeitschrift für die gesamte Versicherungswissenschaft 112 (1), 1-30.
Peer Reviewed
Fakultät Wirtschaftswissenschaften (FW)
Hochschule Coburg
Monika Schnabel
Forschungsreferentin, EU-Referentin
T +49 9561 317 8062
monika.schnabel[at]hs-coburg.de