Amine Trabelsi

Financement

• Subvention. Développement d’un Agent Conversationnel Intelligent pour le Coaching Exécutif. Natural Sciences and Engineering Research Council of Canada (ON, Canada). Alliance Advantage. 455 000 $. (2026-2028).
• Subvention. Cybersecurity Risk Management: A Holistic and Practical Approach. Natural Sciences and Engineering Research Council of Canada (ON, Canada). Alliance Advantage. 5 400 000 $. (2026-2031).
• Subvention. SANTAI: Fiabilisation et transparence des modèles d’intelligence artificielle en santé : application pour l’étude de maladies cardiaques et neuro-dégénératives. Centre National de la Recherche Scientifique (Paris, France). International Research Project. 50 000 EUR. (2026-2029).
• Subvention. EABCD: Explainable AI and Bias Mitigation with Complex Data. Région Auvergne-Rhône-Alpes (Lyon, France). Projet Ambition International. 35 000 EUR. (2026-2028).
• Subvention. Détection automatique des émotions en conversation pour des simulations éducatives en criminologie. Mitacs (Vancouver, Canada). Business Strategy Internship / Stage de stratégie d’entreprise. 15 000 $. (2026).
• Subvention. Soutenir un système de santé apprenant, collaboratif, équitable et durable axé sur les patientes et les patients. Canadian Institutes of Health Research (Ottawa, Canada). Unité de soutien SSA du Québec — Phase II. 95 500 $. (2025-2026).
• Subvention. Modélisation et modération des communautés en ligne. Fonds de recherche du Québec (QC, Canada). FRQNT-Team. 100 000 $. (2024-2026).
• Subvention. Unsupervised Representation Learning and Abstractive Summarization of Stances in Social Media: Towards Explainable Detection Systems for Emerging Rumours. Natural Sciences and Engineering Research Council of Canada (ON, Canada). Discovery. 137 000 $. (2022-2027).
• Subvention. Optimizing Brain Tumour Surveillance in Canada. Canadian Cancer Society (ON, Canada). Challenge Grant. 444 100 $. (2022-2024).
• Subvention. An Ethical Approach to Automatically Explaining Simulation Models via Natural Language Processing. Lakehead University (ON, Canada). VPRI International Research Partnership Award. 10 000 $. (2022-2023).

Publications

Articles

• Eldifrawi, Islam, Wang, Shengrui, Trabelsi, Amine. (2025). FinGrAct: A Framework for FINe-GRrained Evaluation of ACTionability in Explainable Automatic Fact-Checking. arXiv preprint arXiv:2504.05229.
• Branco, Paula, Trabelsi, Amine, Kupferschmidt, Kristina, Äıvodji, Ulrich, Al Osman, Hussein. (2025). Proceedings of the 38th Canadian Conference on Artificial Intelligence.
• Austin, Eric, Makwana, Shraddha, Trabelsi, Amine, Largeron, Christine, Zäıane, Osmar R. (2024). Uncovering flat and hierarchical topics by community discovery on word co-occurrence network. Data Science and Engineering.
• Khosravani, Mohammad, Trabelsi, Amine. (2023). Recent trends in unsupervised summarization. arXiv preprint arXiv:2305.11231.
• Perumal, Anandh, Huang, Chenyang, Trabelsi, Amine, Zäıane, Osmar R. (2020). ANA at SemEval-2020 Task 4: mUlti-task learNIng for cOmmonsense reasoNing (UNION). arXiv preprint arXiv:2006.16403.
• Huang, Chenyang, Trabelsi, Amine, Qin, Xuebin, Farruque, Nawshad, Zäıane, Osmar R. (2019). Seq2emo for multi-label emotion classification based on latent variable chains transformation. arXiv preprint arXiv:1911.02147.
• Trabelsi, Amine. (2018). Unsupervised Mining and Summarization of Polarized Contentious Issues from Online Text.
• Trabelsi, Amine, Zäıane, Osmar R. (2016). Mining contentious documents. Knowledge and Information Systems.
• Trabelsi, Amine, Zäıane, Osmar R. (2015). Extraction and clustering of arguing expressions in contentious text. Data & Knowledge Engineering.
• Trabelsi, Amine. (2010). Configuration et exploitation d'une machine émotionnelle.
• Strobl, Michael, Trabelsi, Amine, Zaiane, Osmar. An Annotated Corpus based on Wikipedia.
• Cao, Peng, Yang, Jinzhu, Tang, Shanshan, Zhao, Dazhe, Zaiane, Osmar, Huang, Min, Trabelsi, Amine. Feature-aware Multi-task feature learning for Predicting Cognitive Outcomes in Alzheimer’s.

Articles de conférence

• Samanta, Kunal, Shohan, Faisal Tareque, Trabelsi, Amine, Khoury, Richard. (2026). Simple Agents, Biased Judges: Efficient Multi-Party Dialogue Generation & The Evaluation Gap. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). DOI
• Benjaa, Nabil, Khalifa, Amir Ben, Shohan, Faisal Tareque, Abdulrazak, Bessam, Trabelsi, Amine, Wang, Shengrui. (2026). Directional Stock Prediction with Temporal Sentiment. Proceedings of the 39th Canadian Conference on Artificial Intelligence.
• Massad, Nicholas, Trabelsi, Amine, Ferland, Francois, Kabanza, Froduald. (2026). VOLTS: Validated Output through Logit Tree Search for Reliable PDDL Planning with Small Language Models. Proceedings of the 39th Canadian Conference on Artificial Intelligence.
• Islam Eldifrawi, Shengrui Wang, Amine Trabelsi. (2026). Can temporal article-level credibility signals improve domain-level credibility prediction?. Findings of the Association for Computational Linguistics: EMNLP 2026. DOI
• Samanta, Kunal, Shohan, Faisal Tareque, Trabelsi, Amine, Khoury, Richard. (2026). Style over Substance: LLM-as-a-Judge Fails to Evaluate Multi-Party Social Dialogue. I Can't Believe It's Not Better: Where Large Language Models Need to Improve, ICLR 2026 Workshop.
• Dubreuil, Anthony, Gourru, Antoine, Largeron, Christine, Trabelsi, Amine. (2025). Are Stereotypes Leading LLMs’ Zero-Shot Stance Detection?. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing.
• Akash, Abu Ubaida, Fahmy, Ahmed, Trabelsi, Amine. (2025). Can Large Language Models Address Open-Target Stance Detection?. Findings of the Association for Computational Linguistics: ACL 2025.
• Sutter, Maia, Gourru, Antoine, Largeron, Christine, Trabelsi, Amine. (2025). Détection non supervisée de position dans les médias sociaux: une approche générique. Extraction et Gestion des Connaissances 2025.
• Eldifrawi, Islam, Wang, Shengrui, Trabelsi, Amine. (2024). Automated justification production for claim veracity in fact checking: A survey on architectures and approaches. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
• Khosravani, Mohammad, Huang, Chenyang, Trabelsi, Amine. (2024). Enhancing argument summarization: Prioritizing exhaustiveness in key point generation and introducing an automatic coverage evaluation metric. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers).
• Sutter, Maia, Gourru, Antoine, Trabelsi, Amine, Largeron, Christine. (2024). Unsupervised stance detection for social media discussions: A generic baseline. Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers).
• Michael Strobl, Amine Trabelsi, Osmar Zaiane. (2023). FREDA: Flexible Relation Extraction Data Annotation. DOI
• Rajendran, Udhaya Kumar, Trabelsi, Amine. (2023). Exploration of contrastive learning strategies toward more robust stance detection. Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis.
• Strobl, Michael, Trabelsi, Amine, Zäıane, Osmar. (2023). FREDA: Flexible Relation Extraction Data Annotation. Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing.
• Rajendran, Udhaya Kumar, Khalifa, Amir Ben, Trabelsi, Amine. (2023). Learning Representations through Contrastive Strategies for a more Robust Stance Detection. 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA).
• Strobl, Michael, Trabelsi, Amine, Zaiane, Osmar R. (2022). Enhanced entity annotations for multilingual corpora. Proceedings of the Thirteenth Language Resources and Evaluation Conference.
• Austin, Eric, Trabelsi, Amine, Largeron⁴, Christine. (2022). Hierarchical Topic Model Inference by Community Discovery on Word. Data Mining: 20th Australasian Conference, AusDM 2022, Western Sydney, Australia, December 12--15, 2022, Proceedings.
• Austin, Eric, Trabelsi, Amine, Largeron, Christine, Zäıane, Osmar R. (2022). Hierarchical topic model inference by community discovery on word co-occurrence networks. Australasian Conference on Data Mining.
• Strobl, Michael, Trabelsi, Amine, Zäıane, Osmar. (2022). Named entity recognition for partially annotated datasets. International Conference on Applications of Natural Language to Information Systems.
• Huang, Chenyang, Trabelsi, Amine, Qin, Xuebin, Farruque, Nawshad, Mou, Lili, Zaiane, Osmar R. (2021). Seq2Emo: A sequence to multi-label emotion classification model. Proceedings of the 2021 conference of the North American chapter of the association for computational linguistics: human language technologies.
• Konar, Anandh, Huang, Chenyang, Trabelsi, Amine, Zaiane, Osmar R. (2020). Ana at semeval-2020 task 4: Multi-task learning for commonsense reasoning (union). Proceedings of the Fourteenth Workshop on Semantic Evaluation.
• Strobl, Michael, Trabelsi, Amine, Zäıane, Osmar R. (2020). Wexea: Wikipedia exhaustive entity annotation. Proceedings of the Twelfth Language Resources and Evaluation Conference.
• Cao, Peng, Tang, Shanshan, Huang, Min, Yang, Jinzhu, Zhao, Dazhe, Trabelsi, Amine, Zaiane, Osmar. (2019). An ensemble framework with $ l_ ${$21$}$ $-norm regularized hypergraph laplacian multi-label learning for clinical data prediction. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
• Huang, Chenyang, Trabelsi, Amine, Zäıane, Osmar R. (2019). Ana at semeval-2019 task 3: Contextual emotion detection in conversations through hierarchical lstms and bert. Proceedings of the 13th international workshop on semantic evaluation.
• Trabelsi, Amine, Zäıane, Osmar R. (2019). Contrastive reasons detection and clustering from online polarized debates. International Conference on Computational Linguistics and Intelligent Text Processing.
• Cao, Peng, Tang, Shanshan, Huang, Min, Yang, Jinzhu, Zhao, Dazhe, Trabelsi, Amine, Zaiane, Osmar. (2019). Feature-aware Multi-task feature learning for Predicting Cognitive Outcomes in Alzheimer's disease. 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).
• Trabelsi, Amine, Zäıane, Osmar R. (2019). Phaitv: A phrase author interaction topic viewpoint model for the summarization of reasons expressed by polarized stances. Proceedings of the International AAAI Conference on Web and Social Media.
• Mehrjardi, Mansour Saffar, Trabelsi, Amine, Zaiane, Osmar R. (2019). Self-attentional models application in task-oriented dialogue generation systems. Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019).
• Huang, Chenyang, Zaiane, Osmar R, Trabelsi, Amine, Dziri, Nouha. (2018). Automatic dialogue generation with expressed emotions. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers).
• Trabelsi, Amine, Zaiane, Osmar. (2018). Unsupervised model for topic viewpoint discovery in online debates leveraging author interactions. Proceedings of the international AAAI conference on web and social media.
• Trabelsi, Amine, Zäıane, Osmar R. (2014). A joint topic viewpoint model for contention analysis. International conference on applications of natural language to data bases/information systems.
• Trabelsi, Amine, Zaiane, Osmar R. (2014). Finding arguing expressions of divergent viewpoints in online debates. Proceedings of the 5th Workshop on Language Analysis for Social Media (LASM).
• Trabelsi, Amine, Zaiane, Osmar R. (2014). Mining contentious documents using an unsupervised topic model based approach. 2014 IEEE International Conference on Data Mining.
• Trabelsi, Amine, Frasson, Claude. (2010). The emotional machine: A machine learning approach to online prediction of user's emotion and intensity. 2010 10th IEEE International Conference on Advanced Learning Technologies.

Rapports

• Université de Sherbrooke. (2025). Adapter les programmes d'études pour tenir compte de l'IA à l'Université de Sherbrooke : recommandations et invitation à l'action. DOI

Autres contributions

Cours enseignés ou supervisés à l'UdeS

• IFT159 - Analyse et programmation. (2023-2026). (3CR).
• IFT607 - Traitement automatique des langues naturelles. (2026). (3CR).
• IFT714 - Traitement automatique des langues naturelles. (2024-2026). (3CR).
• IFT704 - Sujets choisis en intelligence artificielle. (2024-2025). (3CR).
• IFT749 - Sujets choisis en informatique de systèmes. (2023). (3CR).