Published in AI & SOCIETY, 2025
This paper shows how to LLMs offer potential to make archive collections more accessible by automating the keyword extraction process.
Recommended citation: Reusens, M., Adams, A. & Baesens, B. (2025). Large Language Models to make museum archive collections more accessible. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02227-8
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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 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 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 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 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 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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