collaborators

8 papers

cs.HC2026

From Prompts to Context: An Ontology-Driven Framework for Human-Generative AI Collaboration

Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge

Collaborations with Generative AI often begin with a short prompt and end with an opaque output, leaving implicit who was involved, what task was being pursued, which resources wer…

cs.AI2026

From Learning Resources to Competencies: LLM-Based Tagging with Evidence and Graph Constraints

Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge

Linking learning resources to a structured competency framework is key to enabling competency-based search and curriculum analytics in Learning Management Systems (LMS). However, m…

cs.AI2026

When Can We Trust Early Warnings? Leakage-Excluded Early Outcome Prediction from LMS Interaction Logs

Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge

Early-warning models built from Learning Management System (LMS) logs aim to predict end-of-course outcomes early enough to enable timely learner support. However, reported "early"…

cs.IR2026

KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation

Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge

Authoritative competency frameworks such as ESCO, ROME, and O*NET are essential for aligning education with labor market needs, yet their technical complexity and structural hetero…

cs.IR2026

Development of Ontological Knowledge Bases by Leveraging Large Language Models

Le Ngoc Luyen, Marie-Hélène Abel, Philippe Gouspillou

Ontological Knowledge Bases (OKBs) play a vital role in structuring domain-specific knowledge and serve as a foundation for effective knowledge management systems. However, their t…

cs.AI2025

Automated Skill Decomposition Meets Expert Ontologies: Bridging the Granularity Gap with LLMs

Le Ngoc Luyen, Marie-Hélène Abel

This paper investigates automated skill decomposition using Large Language Models (LLMs) and proposes a rigorous, ontology-grounded evaluation framework. Our framework standardizes…