Profile
Teddy Ferdinan
PhD Student
Teddy Ferdinan is a PhD candidate in the Department of Artificial Intelligence at Wrocław University of Science and Technology. He graduated from the Bachelor's degree program in Informatics at Universitas Katolik Musi Charitas, Indonesia, in 2019. Afterwards, he received the NAWA Ignacy Łukasiewicz Scholarship in 2020. In 2023, he earned the Master's degree in Applied Computer Science from Wrocław University of Science and Technology, ranking second in the faculty-level TOP-10 competition for the best graduates of the year. He started his PhD in October 2023, during which he also received the NCN scholarship from project "Personalized Reasoning in Natural Language Processing".
Currently, his research focuses on large language models and natural language processing, specifically continual learning and transfer learning methods, as well as knowledge boundary probing. He has published works in renowned journals and conferences such as Information Fusion, IEEE Intelligent Systems, ACL, and EMNLP, some of which resulted from international collaboration. Most recently, he contributed to the CLARIN-PL research project, PLLuM and its continuation HIVE AI.
Publications13
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
Architectural concepts for integrating fundamental drives and emotions into artificial intelligence
Teddy Ferdinan, Wiktoria M Mieleszczenko-Kowszewicz, Jan Kocoń, Przemysław Kazienko
IEEE 2025
Java source code vulnerability detection using large language model
Dhika R. Anbiya, Teddy Ferdinan, Grzegorz Kołaczek
Procedia Computer Science
Crowdsource, crawl, or generate? Creating SEA-VL, a multicultural vision-language dataset for Southeast Asia
Teddy Ferdinan, Samuel Cahyawijaya
Association for Computational Linguistics
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
Fortifying NLP models against poisoning attacks: The power of personalized prediction architectures
Information Fusion 2025 vol. 114, art. 102692
Into the unknown: Self-learning Large Language Models
Teddy Ferdinan, Jan Kocoń, Przemysław Kazienko
Institute of Electrical and Electronics Engineers
Eagle and Finch: RWKV with matrix-valued states and dynamic recurrence
Bo Peng, Daniel Goldstein, Quentin Anthony, Alon Albalak, Eric Alcaide, Stella Biderman, Eugene Cheah, Du, Xingjian, Teddy Ferdinan, Haowen Hou, Przemysław Kazienko, Kranthi Kiran GV, Jan Kocoń, Bartłomiej Koptyra, Satyapriya Krishna, McClelland, Ronald, Lin, Jiaju, Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Wirawan, Cahya, Stanisław Woźniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jianguo Zhu, Ruijie Zhu
arXiv
Self-training large language models through knowledge detection
Teddy Ferdinan, Przemysław Kazienko, Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
Association for Computational Linguistics
Incidence of heart disease and stroke among patients with bipolar disorder
Dominik M Krzyżanowski, Teddy Ferdinan, R. Szczepanowski, J Kulińska, Marta Palej-Cieplińska, G. Hernandez Ibarburu
2024. vol. 23, suppl. 1, art. zvae098.067
Personalized Models Resistant to Malicious Attacks for Human-centered Trusted AI
Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023)
StudEmo: A Non-aggregated Review Dataset for Personalized Emotion Recognition
Anh Ngo, Argi Candri, Teddy Ferdinan, Jan Kocoń, Wojciech Korczyński
Proceedings of the 1st Workshop on Perspectivist Approaches to NLP @LREC2022