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Manderlier Maxime

Université de Mons - UMONS > Faculté Polytechnique > Service de Management de l'Innovation Technologique

ORCID
0000-0002-5641-9818
Main Referenced Co-authors
Jamet, Henri (2)
LECRON, Fabian  (2)
Shrestha, Yash Raj (2)
Vlachos, Michalis (2)
Main Referenced Keywords
machine learning (3); recommender systems (3); digital education (2); extensive reading (2); large language models (2);
Main Referenced Disciplines
Computer science (9)

Publications (total 9)

The most downloaded
36 downloads
Jamet, H., Manderlier, M., Shrestha, Y. R., & Vlachos, M. (2024). Evaluation and simplification of text difficulty using LLMs in the context of recommending texts in French to facilitate language learning. RecSys '24: Proceedings of the 18th ACM Conference on Recommender Systems, 987-992. doi:10.1145/3640457.3688181 https://hdl.handle.net/20.500.12907/49832

Jamet, H., Manderlier, M., Shrestha, Y. R., & Vlachos, M. (2024). Evaluation and simplification of text difficulty using LLMs in the context of recommending texts in French to facilitate language learning. RecSys '24: Proceedings of the 18th ACM Conference on Recommender Systems, 987-992. doi:10.1145/3640457.3688181
Peer reviewed

Jamet, H., Manderlier, M., Shrestha, Y. R., & Vlachos, M. (October 2024). Evaluation and simplification of text difficulty using LLMs in the context of recommending texts in French to facilitate language learning [Poster presentation]. 18th ACM Conference on Recommender Systems, Bari, Italy.

Manderlier, M. (29 May 2024). Enhancing language learning recommendations: Integrating large language model embeddings in graph neural networks [Paper presentation]. Infortech Day 2024, Mons, Belgium.

Manderlier, M., & Lecron, F. (26 March 2024). Au-delà des recommandations : un voyage ludique au coeur de l’intelligence artificielle explicable [Poster presentation]. Mardi des Chercheurs 2024.

Manderlier, M. (2024). Sérendipité et explicabilité dans les systèmes de recommandation : Deuxième comité d’accompagnement de thèse - Slides. https://orbi.umons.ac.be/handle/20.500.12907/51289

Manderlier, M. (2024). Sérendipité et explicabilité dans les systèmes de recommandation : Deuxième comité d’accompagnement de thèse - Rapport. https://orbi.umons.ac.be/handle/20.500.12907/51288

Manderlier, M., & Lecron, F. (2023). RecSys Challenge 2023: From data preparation to prediction, a simple, efficient, robust and scalable solution. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/48235.

Manderlier, M. (2023). Sérendipité et explicabilité dans les systèmes de recommandation : Premier comité d’accompagnement de thèse - Slides. https://orbi.umons.ac.be/handle/20.500.12907/48265

Manderlier, M. (2023). Sérendipité et explicabilité dans les systèmes de recommandation : Premier comité d’accompagnement de thèse - Rapport. https://orbi.umons.ac.be/handle/20.500.12907/48264

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