  | MURUGARAJ, K., LAMSIYAH, S., & SCHOMMER, C. (2025). Abstractive Summarization of Historical Documents: A New Dataset and Novel Method Using a Domain-Specific Pretrained Model. IEEE Access, 13, 10918-10932. doi:10.1109/access.2025.3528733  Peer Reviewed verified by ORBi |
 | LAMSIYAH, S., Zeinalipour, K., El amrany, S., BRUST, M., Maggini, M., BOUVRY, P., & SCHOMMER, C. (2025). ArabicSense: A Benchmark for Evaluating Commonsense Reasoning in Arabic with Large Language Models. In ArabicSense: A Benchmark for Evaluating Commonsense Reasoning in Arabic with Large Language Models. Abu Dhabi, United Arab Emirates: ACL Anthology. Peer reviewed |
 | Aftiss, A., LAMSIYAH, S., SCHOMMER, C., & El Alaoui, S. O. (2025). Empirical Evaluation of Pre-trained Language Models for Summarizing Moroccan Darija News Articles. In Empirical Evaluation of Pre-trained Language Models for Summarizing Moroccan Darija News Articles. ACL Anthology. Peer reviewed |
  | Aftiss, A., LAMSIYAH, S., SCHOMMER, C., & El Alaoui Ouatik, S. (2024). Abstractive Biomedical Long Document Summarization Through Zero-Shot Prompting. In 2024 Sixth International Conference on Intelligent Computing in Data Sciences (ICDS) (pp. 1-6). Marrakech, Morocco: IEEE. doi:10.1109/icds62089.2024.10756301 Peer reviewed |
LAMSIYAH, S., El Mahdaouy, A., NOURBAKHSH, A., & SCHOMMER, C. (2024). Fine-Tuning a Large Language Model with Reinforcement Learning for Educational Question Generation. In Lecture Notes in Computer Science. recife, Brazil: Springer Nature Switzerland. doi:10.1007/978-3-031-64302-6_30 Peer reviewed |
 | Aftiss, A., LAMSIYAH, S., Ouatik El Alaoui, S., & SCHOMMER, C. (2024). BioMDSum: An Effective Hybrid Biomedical Multi-Document Summarization Method Based on PageRank and Longformer Encoder-Decoder. IEEE Access, 12, 188013 - 188031. doi:10.1109/ACCESS.2024.3514915 Peer Reviewed verified by ORBi |
 | Mahdaouy, A., LAMSIYAH, S., Alami, H., SCHOMMER, C., & Berrada, I. (2023). UM6P & UL at WojoodNER shared task: Improving Multi-Task Learning for Flat and Nested Arabic Named Entity Recognition. In UM6P & UL at WojoodNER shared task: Improving Multi-Task Learning for Flat and Nested Arabic Named Entity Recognition. Singapore, Singapore: Association for Computational Linguistics (ACL). Peer reviewed |
 | LAMSIYAH, S., Mahdaouy, A., Alami, H., Berrada, I., & SCHOMMER, C. (2023). UL & UM6P at ArAIEval Shared Task: Transformer-based model for Persuasion Techniques and Disinformation detection in Arabic. In UL & UM6P at ArAIEval Shared Task: Transformer-based model for Persuasion Techniques and Disinformation detection in Arabic (pp. 777–782). Singapore, Singapore: Association for Computational Linguistics (ACL). Peer reviewed |
 | SCHOMMER, C., LAMSIYAH, S., & NOUZRI, S. (2023). Über den Einsatz von Generative.AI für die Lehre. Luxemburger Wort. |
 | LAMSIYAH, S., MURUGARAJ, K., & SCHOMMER, C. (2023). Historical-Domain Pre-trained Language Model for Historical Extractive Text Summarization. In Historical-Domain Pre-trained Language Model for Historical Extractive Text Summarization. London, United Kingdom: https://avestia.com/. doi:10.11159/cist23.152 Peer reviewed |
 | LAMSIYAH, S., & SCHOMMER, C. (2023). A Comparative Study of Sentence Embeddings for Unsupervised Extractive Multi-document Summarization. In Artificial Intelligence and Machine Learning (pp. 78--95). Cham, Unknown/unspecified: Springer Nature Switzerland. doi:10.1007/978-3-031-39144-6_6 Peer reviewed |
 | LAMSIYAH, S., El Mahdaouy, A., & SCHOMMER, C. (2023). Can Anaphora Resolution Improve Extractive Query-Focused Multi-Document Summarization? IEEE Access, 1-1. doi:10.1109/ACCESS.2023.3314524 Peer Reviewed verified by ORBi |
 | LAMSIYAH, S., El Mahdaouy, A., Alami, H., Berrada, I., & SCHOMMER, C. (2023). UL \& UM6P at SemEval-2023 Task 10: Semi-Supervised Multi-task Learning for Explainable Detection of Online Sexism. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023) (pp. 644--650). Toronto, Canada, Unknown/unspecified: Association for Computational Linguistics. doi:10.18653/v1/2023.semeval-1.88 Peer reviewed |
 | El Mahdaouy, A., Alami, H., LAMSIYAH, S., & Berrada, I. (2023). UM6P at SemEval-2023 Task 12: Out-Of-Distribution Generalization Method for African Languages Sentiment Analysis. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023) (pp. 1004--1010). Toronto, Canada, Unknown/unspecified: Association for Computational Linguistics. doi:10.18653/v1/2023.semeval-1.138 Peer reviewed |
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