Jan Kocon

@pwr.edu.pl

Department of Artificial Intelligence
Wroclaw University of Science and Technology

Jan Kocon


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https://researchid.co/jankocon
I'm an Assistant Professor in the Department of Artificial Intelligence at the Wroclaw University of Science and Technology, where I earned both my Ph.D. in computer science (2018) and M.Sc. Eng. degree (2012). I am the AI/ML Team Leader and Senior ML/NLP Data Scientist for the CLARIN-BIZ and PLLuM projects. My passion for natural language processing (NLP) has spanned over a decade, with a keen interest in machine learning techniques. I've published over 90 scientific papers at prominent conferences, including ACL, ICDM, EMNLP, and more. My current endeavors involve pioneering deep learning models for subjective tasks such as emotion and sentiment analysis. I'm also delving into cross-lingual knowledge transfer and language-agnostic models. My contributions have been integral to CrisisDetector, StockBrief, Sentimenti, CLARIN-PL, and PLLuM projects. I enjoy imparting knowledge on data science, AI's role in NLP, and building sophisticated deep neural networks.

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Science Applications, Signal Processing
81

Scopus Publications

6932

Scholar Citations

25

Scholar h-index

51

Scholar i10-index

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

  • What properties of reasoning supervision are associated with improved downstream model quality?
    M Langner, D Pihulski, J Eliasz, M Rajkowski, P Kazienko, M Piasecki, ...
    arXiv preprint arXiv:2605.13290 , 2026
    2026
  • Exploring the future of psychometrics from a Large Language Model perspective: A case study analysis
    W Mieleszczenko-Kowszewicz, J Bielaniewicz, K Kanclerz, J Kocoń, ...
    Computers in Human Behavior Reports 22, 101060 , 2026
    2026
  • Breaking the Illusion of Reasoning in Polish LLMs: Quality over Quantity of Thought
    D Pihulski, M Langner, J Eliasz, P Kazienko, J Kocon, T Ferdinan
    Findings of the Association for Computational Linguistics: EACL 2026, 1796-1811 , 2026
    2026
    Citations: 1
  • Architectural Concepts for Integrating Fundamental Drives and Emotions Into Artificial Intelligence
    T Ferdinan, W Mieleszczenko-Kowszewicz, J Kocoń, P Kazienko
    IEEE Intelligent Systems 40 (6), 91-98 , 2025
    2025
    Citations: 1
  • Typology of Image Crises Using Large Language Models: A Novel Approach to Crisis Classification
    G Chodak, D Tworzydło, A Szczęsny, P Kazienko, O Kaszyca, K Bilski, ...
    Journal of Contingencies and Crisis Management 33 (4), e70092 , 2025
    2025
    Citations: 1
  • CLARIN-PL: a user centred language technology infrastructure: M. Piasecki et al.
    M Piasecki, A Dziob, A Janz, J Kocoń, T Naskrȩt, M Oleksy, E Rudnicka, ...
    Language Resources and Evaluation 59 (4), 4493-4528 , 2025
    2025
    Citations: 4
  • The PLLuM Instruction Corpus
    P Pęzik, F Żarnecki, K Kaczyński, A Cichosz, Z Deckert, M Garnys, ...
    arXiv preprint arXiv:2511.17161 , 2025
    2025
    Citations: 1
  • PLLuM: A Family of Polish Large Language Models
    J Kocoń, M Piasecki, A Janz, T Ferdinan, Ł Radliński, B Koptyra, M Oleksy, ...
    arXiv preprint arXiv:2511.03823 , 2025
    2025
    Citations: 5
  • Divide, Cache, Conquer: Dichotomic Prompting for Efficient Multi-Label LLM-Based Classification
    M Langner, J Eliasz, E Rudnicka, J Kocoń
    arXiv preprint arXiv:2511.03830 , 2025
    2025
    Citations: 1
  • Global piqa: Evaluating physical commonsense reasoning across 100+ languages and cultures
    TA Chang, C Arnett, A Eldesokey, A Sadallah, A Kashar, A Daud, ...
    arXiv preprint arXiv:2510.24081 , 2025
    2025
    Citations: 11
  • Language, Culture, and Ideology: Personalizing Offensiveness Detection in Political Tweets with Reasoning LLMs
    D Pihulski, J Kocoń
    arXiv preprint arXiv:2510.02351 , 2025
    2025
    Citations: 1
  • LLMSQL: Upgrading WikiSQL for the LLM Era of Text-to-SQL
    D Pihulski, K Charchut, V Novogrodskaia, J Kocoń
    arXiv preprint arXiv:2510.02350 , 2025
    2025
    Citations: 1
  • Predicting stock prices with ChatGPT-annotated Reddit sentiment: Hype or reality?
    M Kmak, K Chmurzyński, K Matejuk, P Kotzbach, J Kocoń
    International Conference on Computational Science, 307-322 , 2025
    2025
    Citations: 1
  • Enhancing AI Face Realism: Cost-Efficient Quality Improvement in Distilled Diffusion Models with a Fully Synthetic Dataset
    J Wąsala, B Wrzalski, K Noculak, Y Tarasenko, O Krupa, J Kocoń, ...
    International Conference on Computational Science, 119-134 , 2025
    2025
    Citations: 1
  • SupResDiffGAN a new approach for the Super-Resolution task
    D Kopeć, W Kozłowski, M Wizerkaniuk, D Krutul, J Kocoń, M Zięba
    International Conference on Computational Science, 66-80 , 2025
    2025
    Citations: 6
  • AggTruth: Contextual Hallucination Detection using Aggregated Attention Scores in LLMs
    P Matys, J Eliasz, K Kiełczyński, M Langner, T Ferdinan, J Kocoń, ...
    International Conference on Computational Science, 227-243 , 2025
    2025
    Citations: 3
  • Backtranslation and paraphrasing in the llm era? comparing data augmentation methods for emotion classification
    Ł Radliński, M Guściora, J Kocoń
    International Conference on Computational Science, 3-17 , 2025
    2025
    Citations: 4
  • Integrating personalized and contextual information in fine-grained emotion recognition in text: A multi-source fusion approach with explainability
    A Ngo, J Kocoń
    Information Fusion 118, 102966 , 2025
    2025
    Citations: 10
  • Improving llm-based recommender systems with user-controllable profiles
    S Woźniak, J Duszenko, J Kocoń, P Kazienko
    Companion Proceedings of the ACM on Web Conference 2025, 2102-2111 , 2025
    2025
    Citations: 9
  • Fortifying nlp models against poisoning attacks: The power of personalized prediction architectures
    T Ferdinan, J Kocoń
    Information Fusion 114, 102692 , 2025
    2025
    Citations: 9

MOST CITED SCHOLAR PUBLICATIONS

  • Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
    A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
    Transactions on machine learning research , 2023
    2023
    Citations: 2646
  • Rwkv: Reinventing rnns for the transformer era
    B Peng, E Alcaide, Q Anthony, A Albalak, S Arcadinho, S Biderman, ...
    Findings of the association for computational linguistics: EMNLP 2023, 14048 … , 2023
    2023
    Citations: 1301
  • ChatGPT: Jack of all trades, master of none
    J Kocoń, I Cichecki, O Kaszyca, M Kochanek, D Szydło, J Baran, ...
    Information fusion 99, 101861 , 2023
    2023
    Citations: 1198
  • Offensive, aggressive, and hate speech analysis: From data-centric to human-centered approach
    J Kocoń, A Figas, M Gruza, D Puchalska, T Kajdanowicz, P Kazienko
    Information Processing & Management 58 (5), 102643 , 2021
    2021
    Citations: 169
  • Eagle and finch: Rwkv with matrix-valued states and dynamic recurrence
    B Peng, D Goldstein, Q Anthony, A Albalak, E Alcaide, S Biderman, ...
    arXiv preprint arXiv:2404.05892 , 2024
    2024
    Citations: 162
  • Personalized large language models
    S Woźniak, B Koptyra, A Janz, P Kazienko, J Kocoń
    2024 IEEE International Conference on Data Mining Workshops (ICDMW), 511-520 , 2024
    2024
    Citations: 77
  • Multi-level sentiment analysis of PolEmo 2.0: Extended corpus of multi-domain consumer reviews
    J Kocoń, P Miłkowski, M Zaśko-Zielińska
    Proceedings of the 23rd Conference on Computational Natural Language … , 2019
    2019
    Citations: 73
  • Liner2–a customizable framework for proper names recognition for Polish
    M Marcińczuk, J Kocoń, M Janicki
    Intelligent Tools for Building a Scientific Information Platform: Advanced … , 2013
    2013
    Citations: 61
  • Learning personal human biases and representations for subjective tasks in natural language processing
    J Kocoń, M Gruza, J Bielaniewicz, D Grimling, K Kanclerz, P Miłkowski, ...
    2021 IEEE international conference on data mining (ICDM), 1168-1173 , 2021
    2021
    Citations: 60
  • Human-centered neural reasoning for subjective content processing: Hate speech, emotions, and humor
    P Kazienko, J Bielaniewicz, M Gruza, K Kanclerz, K Karanowski, ...
    Information Fusion 94, 43-65 , 2023
    2023
    Citations: 55
  • Personal bias in prediction of emotions elicited by textual opinions
    P Miłkowski, M Gruza, K Kanclerz, P Kazienko, D Grimling, J Kocon
    Proceedings of the 59th annual meeting of the association for computational … , 2021
    2021
    Citations: 54
  • Cross-lingual deep neural transfer learning in sentiment analysis
    K Kanclerz, P Miłkowski, J Kocoń
    Procedia Computer Science 176, 128-137 , 2020
    2020
    Citations: 54
  • Controversy and conformity: from generalized to personalized aggressiveness detection
    K Kanclerz, A Figas, M Gruza, T Kajdanowicz, J Kocoń, D Puchalska, ...
    Proceedings of the 59th Annual Meeting of the Association for Computational … , 2021
    2021
    Citations: 49
  • Clarin-emo: Training emotion recognition models using human annotation and chatgpt
    B Koptyra, A Ngo, Ł Radliński, J Kocoń
    International conference on computational science, 365-379 , 2023
    2023
    Citations: 44
  • What if ground truth is subjective? personalized deep neural hate speech detection
    K Kanclerz, M Gruza, K Karanowski, J Bielaniewicz, P Miłkowski, J Kocoń, ...
    Proceedings of the 1st Workshop on Perspectivist Approaches to NLP@ LREC2022 … , 2022
    2022
    Citations: 40
  • plWordNet as a basis for large emotive lexicons of Polish
    A Janz, J Kocon, M Piasecki, M Zasko-Zielinska
    Proceedings of Human Language Technologies as a Challenge for Computer … , 2017
    2017
    Citations: 37
  • Neuro-symbolic models for sentiment analysis
    J Kocoń, J Baran, M Gruza, A Janz, M Kajstura, P Kazienko, W Korczyński, ...
    International conference on computational science, 667-681 , 2022
    2022
    Citations: 35
  • Multiemo: Multilingual, multilevel, multidomain sentiment analysis corpus of consumer reviews
    J Kocoń, P Miłkowski, K Kanclerz
    International Conference on Computational Science, 297-312 , 2021
    2021
    Citations: 34
  • Studemo: A non-aggregated review dataset for personalized emotion recognition
    A Ngo, A Candri, T Ferdinan, J Kocoń, W Korczynski
    Proceedings of the 1st Workshop on Perspectivist Approaches to NLP@ LREC2022 … , 2022
    2022
    Citations: 28
  • Multitask personalized recognition of emotions evoked by textual content
    P Miłkowski, S Saganowski, M Gruza, P Kazienko, M Piasecki, J Kocoń
    2022 IEEE International Conference on Pervasive Computing and Communications … , 2022
    2022
    Citations: 27