The library will be closed between August 10, 2026 and August 16, 2026. During this period, it will be possible to upload publications, but all other services will be suspended.
Debreceni Egyetem. Informatikai Kar. Adattudomány és Vizualizáció Tanszék / University of Debrecen. Faculty of Informatics. Adattudomány és Vizualizáció Tanszék
Pándy, Á.,
Lakatos, R.,
Hajdu, A.:
Error-Driven Prompt Optimization for Arithmetic Reasoning: A Code Generation Approach Using On-Premises Small Language Models on Tabular Data.
IEEE Access. [Epub ahead of print], 1- 16, 2026.
Lakatos, R.,
Pollner, P.,
Hajdu, A.,
Joó, T.:
Investigating the Performance of Retrieval-Augmented Generation and Domain-Specific Fine-Tuning for the Development of AI-Driven Knowledge-Based Systems.
Mach. Learn. Knowl. Extr. 7 (1), 1-18, (article identifier: 15), 2025.
Lakatos, R.,
Pollner, P.,
Hajdu, A.,
Joó, T.:
A multimodal deep learning architecture for smoking detection with a small data approach.
Front. Artif. Intell. 7, 1-8, (article identifier: 1326050), 2024.
Bogacsovics, G.,
Harangi, B.,
Beregi-Kovács, M.,
Kupás, D.,
Lakatos, R.,
Serbán, N. D.,
Tiba, A.,
Tóth, J.:
Assessing Conventional and Deep Learning-Based Approaches for Named Entity Recognition in Unstructured Hungarian Medical Reports.
In: 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI). Ed.: Kovács Levente, Liberios Vokorokos, IEEE, Piscataway, 77-82, 2024. ISBN: 9798350317206
Lakatos, R.,
Urbán, E. K.,
Szabó, Z. J.,
Pozsga, J.,
Csernai, E.,
Hajdu, A.:
Designing Prompts and Creating Cleaned Scientific Text for Retrieval Augmented Generation for More Precise Responses from Generative Large Language Models.
In: 2024 IEEE 3rd Conference on Information Technology and Data Science (CITDS) / Hajdu Andras, Institute of Electrical and Electronics Engineers, Piscataway (NJ), 1-6, 2024.
Pándy, Á.,
Lakatos, R.,
Pollner, P.,
Csernai, E.,
Hajdu, A.:
Investigating the Influence of Hyperparameters on the Optimal Time-Series Prediction Ability of Generative Large Language Models.
In: 2024 IEEE 3rd Conference on Information Technology and Data Science (CITDS), Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 158-163, 2024. ISBN: 9798350387889
Nagy, J.,
Hajdu, A.,
Bogacsovics, G.,
Bojtor, C.,
Illés, Á.,
Lakatos, R.,
Mészáros, L.:
Precíziós gazdálkodásban használható adatelemzés alapú növénytermesztési döntéstámogató rendszer fejlesztés.
In: LXV. Georgikon Napok Tudományos Konferencia = 65th Georgikon Days Scientific Conference /szerk. Pőr Csilla, Szabó-Soós Adrienn, Szabó Péter, Magyar Agrár- és Élettudományi Egyetem Georgikon Campus, Keszthely, 133-134, 2024. ISBN: 9786156338105
Lakatos, R.,
Bogacsovics, G.,
Hajdu, A.:
Predicting the direction of the oil price trend using sentiment analysis.
In: IEEE 2nd Conference on Information Technology and Data Science (CITDS) : Proceedings. Ed.: Fazekas István, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 177-182, 2022.
