Chapitre de livre
Nyamen Tato A., Nkambou R.
(2026).
Leveraging LLMs for Bayesian and Deep Knowledge Tracing in the Logic-Muse Intelligent Tutoring System.
Generative Systems and Intelligent Tutoring Systems
( p.182–191 )
: Springer, Cham
Article de colloque
Nyamen Tato A., Nkambou R.
(2026).
Leveraging LLMS for Bayesian and deep knowledge tracing in the logic-muse intelligent tutoring system.
International Conference on Intelligent Tutoring Systems
(p.182-191).: Cham: Springer Nature Switzerland.
Article de colloque
Tamkodjou Tchio G., Nkambou R., Psyché V., Nyamen Tato A.
(2026).
Enhancing Pilot Training and Decision-Making Using Ontologies: A Cognitive Assistance Approach.
International Conference on Intelligent Tutoring Systems
(p.59-73).: Cham: Springer Nature Switzerland.
Chapitre de livre
Kengne-Talling S., Nkambou R., Nyamen Tato A., Lacourarie C.
(2025).
Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT-LLM in Chaotic Environments.
Advances and Trends in Artificial Intelligence.Theory and Applications
( p.419–431 )
: Springer, Singapore
Chapitre de livre
Nyamen Tato A., Nkambou R.
(2025).
Can LLMs Generate Accurate Bayesian Networks to Enhance Knowledge Tracing ?.
Artificial Intelligence in Education
( p.319–332 )
: Springer, Cham
Article de colloque
Kengne D., Nkambou R., Nyamen Tato A., Lacourarie C.
(2025).
Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT-LLM in Chaotic Environments.
International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems
(p.419-431).Singapour, Singapour: Singapore: Springer Nature Singapore.