Published in International Conference on Research Challenges in Information Science, 2022
This paper benchmarks several outlier detection methods.
Recommended citation: 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.
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Published in Journal of Business Analytics, 2023
This paper uses topic modelling to analyze innovation within Flemish companies based on their websites.
Recommended citation: 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.
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Published in EMNLP, 2023
This paper investigates the transferability of debiasing techniques across different languages within multilingual models.
Recommended citation: 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).
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Published in EMNLP, 2023
This paper introduces a new exemplar selection method named SEER for in-context hybridQA.
Recommended citation: 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).
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Published in TOP, 2024
This paper introduces a three-step weak supervision approach for predicting demographics of Twitter users.
Recommended citation: Tonglet, J., Jehoul, A., Reusens, M., Reusens, M., & Baesens, B. (2024). Predicting the demographics of Twitter users with programmatic weak supervision. Top, 1-37.
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Published in Expert Systems with Applications, 2024
This paper includes a benchmark study comparing different techniques for text classification.
Recommended citation: 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.
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Published:
I presented our paper ‘Evaluating text classification: A benchmark study’. Abstract
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This was an (oral) presentation of the paper ‘Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques’
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I presented the results of the research collaboration between the VSA and the KU Leuven. This was a combination of work done by several thesis groups over the last years. The talk was held in Dutch. URL slides
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I held a talk on the academic perspective of GenAI at the alumni day for postgraduate studies in Big Data and Analytics at the KU Leuven. More specifically, on the transferability of debiasing in a multilingual language model. URL
Undergraduate course, KU Leuven, Faculty of Business and Economics, 2021
I have been the TA of Principles for Database Management (6ECTS) at the KU Leuven from 2021-2025 (expected). I am responsible for the assignment, which is currently orally defended. The course includes more than 200 students.
Graduate Course, KU Leuven, Department of Business and Economics, 2023
I have given a guest lecture on applications of Natural Language Processing in the course Data Science for Business (6 ECTs) to Graduate students.
Graduate Course (Advanced Master and Postgraduate), KU Leuven, Department of Business and Economics, 2024
I have given a guest lecture on applications of Natural Language Processing in the course Business Analytics (6 ECTs).