26 citations · 26 across the 6 of their papers we have counts for
10 papers
Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
Clémence Réda, Tomas Rigaux, Hiba Bederina +3
A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items personalized to the user's preferences, but which also mi…
Live Knowledge Tracing: Real-Time Adaptation using Tabular Foundation Models
Mounir Lbath, Alexandre Parésy, Abdelkayoum Kaddouri +2
Deep knowledge tracing models have achieved significant breakthroughs in modeling student learning trajectories. However, these architectures require substantial training time and…
Diversified recommendations of cultural activities with personalized determinantal point processes
Carole Ibrahim, Hiba Bederina, Daniel Cuesta +3
While optimizing recommendation systems for user engagement is a well-established practice, effectively diversifying recommendations without negatively impacting core business metr…
Bayesian-Guided Diversity in Sequential Sampling for Recommender Systems
Hiba Bederina, Jill-Jênn Vie
The challenge of balancing user relevance and content diversity in recommender systems is increasingly critical amid growing concerns about content homogeneity and reduced user eng…
A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents
Jean Vassoyan, Anan Schütt, Jill-Jênn Vie +3
Massive Open Online Courses (MOOCs) have greatly contributed to making education more accessible. However, many MOOCs maintain a rigid, one-size-fits-all structure that fails to ad…
DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills
Benoît Choffin, Fabrice Popineau, Yolaine Bourda +1
Spaced repetition is among the most studied learning strategies in the cognitive science literature. It consists in temporally distributing exposure to an information so as to impr…