Profil
Jan Kocoń
Adiunkt
Jan Kocoń is an Assistant Professor at the Wroclaw University of Science and Technology, where he received a Ph.D. degree in computer science (2018) and an MSc. Eng. degree (2012). He is also AI/ML Team Leader and Senior ML/NLP Data Scientist in the CLARIN-BIZ project. He has worked on natural language processing (NLP) for over a decade, especially using machine learning methods. He is the author of more than 60 scientific publications, presented at conferences such as ACL, ICDM, CoNLL, COLING, PerCOM, ICCS, KES, LREC, RANLP, and GWC. He is currently working on advanced personalized models based on deep learning in subjective tasks, such as emotion, sentiment, hate speech, or humor recognition. He also works on cross-lingual knowledge transfer and the application of language-agnostic models. He actively participated in the following projects using machine learning-based solutions: SYNAT, NEKST, CLARIN-PL, Parthenos, AZON, Sentimenti, CLARIN-BIZ, Q-Travel, and AI Tech. He lectures on an introduction to data science, the application of artificial intelligence in natural language processing, and the construction of advanced deep neural network models. Winner of HackYeah 2021 - the largest hackathon in Europe - in a task related to optimizing the construction of a power plant based on renewable energy sources for hydrogen production.
Grupy badawcze
Wykształcenie
- 2012
magister informatyki
Politechnika Wrocławska
- 2018
doktor informatyki, sztuczna inteligencja
Politechnika Wrocławska
Publikacje98
Artificial intelligence overload: a multilevel taxonomy and the path forward
Przemysław Kazienko, Wiktoria M Mieleszczenko-Kowszewicz, Jan Kocoń, Beata Bajcar, Julian Sienkiewicz, Janusz A Hołyst, Philipp Mayr, Ingo Frommholz, Erik Cambria
IEEE 2026
Exploring the future of psychometrics from a Large Language Model perspective: A case study analysis
Wiktoria M. Mieleszczenko-Kowszewicz, Julita Bielaniewicz, Jan Kocoń, Przemysław Kazienko, Kamil Kanclerz
Computers in Human Behavior Reports 2026 vol. 22, art. 101060
Breaking the illusion of reasoning in Polish LLMs: quality over quantity of thought
Dzmitry Pihulski, Mikołaj Langner, Jan Eliasz, Przemyslaw Kazienko, Jan Kocoń, Teddy Ferdinan, T Ferdinan
Association for Computational Linguistics
CLARIN‑PL: a user centred language technology infrastructure
Maciej Piasecki, Agnieszka Dziob-Zadworna, Arkadiusz Janz, Jan Kocoń, Tomasz Naskręt, Marcin Ł Oleksy, Ewa K Rudnicka, Tomasz Walkowiak, Jan A Wieczorek, Krzysztof Hwaszcz
Language Resources and Evaluation 2025 vol. 59, [ Publikacja zarejestrowana jako preonline dn. 02.06.2025, rok zaliczenia 2025. Wersja ostateczna zarejestrowana 09.12.2025, rok zaliczenia 2025
LLMSQL: Upgrading WikiSQL for the LLM Era of text-to-SQL
Dzmitry Pihulski, Karol Charchut, Viktoria Novogrodskaia, Jan Kocoń
Institute of Electrical and Electronics Engineers
Language, culture, and ideology: personalizing offensiveness detection in political tweets with reasoning LLMs
Institute of Electrical and Electronics Engineers
Divide, cache, conquer: dichotomic prompting for efficient multi-label LLM-based classification
Mikołaj Langner, Jan K Eliasz, Ewa K Rudnicka, Jan Kocoń
Institute of Electrical and Electronics Engineers
Architectural concepts for integrating fundamental drives and emotions into artificial intelligence
Teddy Ferdinan, Wiktoria M Mieleszczenko-Kowszewicz, Jan Kocoń, Przemysław Kazienko
IEEE 2025
Typology of Image Crises Using Large Language Models: A Novel Approach to Crisis Classification
Grzegorz Chodak, Aleksander P Szczęsny, Przemysław Kazienko, Oliwier Kaszyca, Marcin Ł Oleksy, Mateusz Kochanek, Dominika Szydło, Igor Cichecki, Wiktoria M Mieleszczenko-Kowszewicz, Ewa Dzięcioł, Tomasz Kajdanowicz, Maciej Piasecki, Jan Kocoń, Dariusz Tworzydło, Kajetan Bilski, Kaja Matuszak, Przemysław Palacz
Journal of Contingencies and Crisis Management 2025 vol. 33, nr 4, art. e70092
Predicting stock prices with ChatGPT-annotated Reddit sentiment: hype or reality?
Mateusz Kmak, Kamil Chmurzyński, Kamil Matejuk, Paweł Kotzbach, Jan Kocoń
Lecture notes in computer science
SupResDiffGAN a new approach for the super-resolution task
Dawid A. Kopeć, Wojciech M Kozłowski, Maciej Wizerkaniuk, Dawid Krutul, Jan Kocoń, Maciej M Zięba
Lecture notes in computer science
Enhancing AI Face Realism: Cost-Efficient Quality Improvement in Distilled Diffusion Models with a Fully Synthetic Dataset
Jakub Wąsala, Bartłomiej Wrzalski, Kornelia Noculak, Yuliia Tarasenko, Oliwer Krupa, Jan Kocoń, Grzegorz Chodak
arXiv
Backtranslation and paraphrasing in the LLM era? Comparing data augmentation methods for emotion classification
Łukasz Radliński, Mateusz Guściora, Jan Kocoń
Springer Nature Switzerland AG
AggTruth: contextual hallucination detection using aggregated attention scores in LLMs
Piotr J. Matys, Jan K Eliasz, Konrad M Kiełczyński, Mikołaj Langner, Teddy Ferdinan, Jan Kocoń, Przemysław Kazienko
Springer Nature Switzerland AG
Improving LLM-Based Recommender Systems with User-Controllable Profiles
Stanisław J. Woźniak, Jacek J Duszenko, Jan Kocoń, Przemysław Kazienko
WWW 2025
Fortifying NLP models against poisoning attacks: The power of personalized prediction architectures
Information Fusion 2025 vol. 114, art. 102692
PolEval 2024 Task 2: Emotion and sentiment recognition
Institute of Computer Science, Polish Academy of Sciences
Small language models for emotion recognition in Polish stock market investor opinions
Bartłomiej Koptyra, Marcin Ł Oleksy, Ewa Dzięcioł, Jan Kocoń
Institute of Electrical and Electronics Engineers
Wyświetlono 20 z 98