Hello!
I am a PhD student at Copenhagen University part of the CoAStal NLP group under the supervision of Anders Søgaard. My main research interests are on Brain Activity-Language Model alignment, Explainable AI, Optical Character Recognition, Cultural NLP applications, and Ethics.
My master's degree in Natural Language Processing from Uppsala University provided a strong foundation for this research journey 🗺. My thesis was in Argument Mining and supervised by Joakim Nivre. I also have hands-on experience as a research assistant, data scientist and software engineer 💻.
Selected Publications
2023
Li*, J., Karamolegkou*, A., Kementchedjhieva, Y., Abdou, M., Lehmann, S., & Søgaard, A. . Structural Similarities Between Language Models and Neural Response Measurements (Neurreps@Neurips 2023, to appear).
Karamolegkou, A., Li, J., Zhou, L., & Søgaard, A. Copyright Violations and Large Language Models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023, to appear).
Karamolegkou, Antonia, Mostafa Abdou, and Anders Søgaard. Mapping Brains with Language Models: A Survey . Findings of the Association for Computational Linguistics: ACL 2023.
2022
Due Jeppe, Pedersen Marianne, Antonsen Sussie, Rommedahl Joen, Agerbo Esben, Mortensen Preben Bo, Sørensen Henrik, Lotz Jonas, Piqueras Laura, Fierro Constanza, Karamolegkou Antonia, Igel Christian, Rust Phillip, Søgaard Anders, Pedersen Carsten. 2022. Towards More Comprehensive Nationwide Familial Aggregation Studies in Denmark . Scandinavian Journal of Public Health.
2021
Antonia Karamolegkou, Sara Stymne. Investigation of Transfer Languages for Parsing Latin: Italic Branch vs. Hellenic Branch.. In Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa). Pages 315-320.
Aris Fergadis, Dimitris Pappas, Antonia Karamolegkou, Haris Papageorgiou. Argumentation Mining in Scientific Literature for Sustainable Development. In Proceedings of the 8th Workshop on Argument Mining. Punta Cana, Dominican Republic: Association for Computational Linguistics. Pages 100– 111.