| 2026 | AIED | Estimating Learners' Skill Acquisition Without Temporal Information. | Ryosuke Nagai, Kyohei Atarashi, Koh Takeuchi, Jill-Jnn Vie, Hisashi Kashima |
| 2026 | LAK | Robust Post-hoc Score Allocation in Exams. | Naoyuki Kita, Jill-Jnn Vie, Koh Takeuchi, Hisashi Kashima |
| 2025 | EDM | AlgoAce: Retrieval-Augmented Generation for Assistance in Competitive Programming. | Anav Agrawal, Jill-Jnn Vie |
| 2024 | EDM | Optimizing Human Learning using Reinforcement Learning. | Samuel Girard, Jill-Jnn Vie, Franoise Tort, Amel Bouzeghoub |
| 2024 | LAK | Adaptation of the Multi-Concept Multivariate Elo Rating System to Medical Students' Training Data. | Erva Nihan Kandemir, Jill-Jnn Vie, Adam Sanchez-Ayte, Olivier Palombi, Franck Ramus |
| 2023 | EDM | Towards Scalable Adaptive Learning with Graph Neural Networks and Reinforcement Learning. | Jean Vassoyan, Jill-Jnn Vie, Pirmin Lemberger |
| 2023 | ICCE | Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model. | Jill-Jnn Vie, Hisashi Kashima |
| 2022 | AAAI | Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. | Sein Minn, Jill-Jnn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu |
| 2019 | AAAI | Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. | Jill-Jnn Vie, Hisashi Kashima |
| 2019 | EDM | DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills. | Benot Choffin, Fabrice Popineau, Yolaine Bourda, Jill-Jnn Vie |
| 2018 | ICDM | Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing. | Sein Minn, Yi Yu, Michel C. Desmarais, Feida Zhu, Jill-Jnn Vie |
| 2018 | ITS | Preface. | Fabrice Popineau, Michal Valko, Jill-Jnn Vie |
| 2018 | ITS | Knowledge Tracing Machines: Towards an Unification of DKT, IRT & PFA. | Jill-Jnn Vie |
| 2017 | ICDAR | Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. | Jill-Jnn Vie, Florian Yger, Ryan Lahfa, Basile Clement, Kvin Cocchi, Thomas Chalumeau, Hisashi Kashima |
| 2015 | EDM | Predicting Performance on Dichotomous Questions: Comparing Models for Large-Scale Adaptive Testing. | Jill-Jnn Vie, Fabrice Popineau, Jean-Bastien Grill, Eric Bruillard, Yolaine Bourda |