Reusens, M., Stevens, A., Tonglet, J., De Smedt, J., Verbeke, W., Vanden Broucke, S., & Baesens, B. (2024). Evaluating text classification: A benchmark study. Expert Systems with Applications, 124302.
Tonglet, J., Jehoul, A., Reusens, M., Reusens, M., & Baesens, B. (2024). Predicting the demographics of Twitter users with programmatic weak supervision. Top, 1-37.
Tonglet, J., Reusens, M., Borchert, P., & Baesens, B. (2023, December). SEER: A Knapsack approach to Exemplar Selection for In-Context HybridQA. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (pp. 13569-13583).
Reusens, M., Borchert, P., Mieskes, M., De Weerdt, J., & Baesens, B. (2023, December). Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (pp. 2887-2896).
Crijns, A., Vanhullebusch, V., Reusens, M., Reusens, M., & Baesens, B. (2023). Topic modelling applied on innovation studies of Flemish companies. Journal of Business Analytics, 6(4), 243-254.
Tiukhova, E., Reusens, M., Baesens, B., & Snoeck, M. (2022, May). Benchmarking conventional outlier detection methods. In International Conference on Research Challenges in Information Science (pp. 597-613). Cham: Springer International Publishing.
Talk at Spring Fest, Leuven, Belgium
Talk at Dag van het netwerk Statistiek Vlaanderen, Brussel, Belgium
Conference proceedings talk at EMNLP, 8 Sentosa Gateway, Singapore
Conference proceedings talk at IFORS, Santiago, Chile
Talk at Statistics Flanders Seminar, Leuven, Belgium
In total, I have guided 16 master theses at the KU Leuven. Two of these projects have led to a journal publication, and one of them led to a publication at EMNLP 2023. Apart from this, I have also guided summer interns.