3 papers
cs.CL2026
Conversational Control with Ontologies for Large Language Models: A Lightweight Framework for Constrained Generation
Barbara Gendron, Gaël Guibon, Mathieu d'Aquin
Conversational agents based on Large Language Models (LLMs) have recently emerged as powerful tools for human-computer interaction. Nevertheless, their black-box nature implies cha…
cs.AI2025
Towards Ontology-Based Descriptions of Conversations with Qualitatively-Defined Concepts
Barbara Gendron, Gaël Guibon, Mathieu D'aquin
The controllability of Large Language Models (LLMs) when used as conversational agents is a key challenge, particularly to ensure predictable and user-personalized responses. This…
cs.LG2024
Transfer Learning for Deep Learning-based Prediction of Lattice Thermal Conductivity
L. Klochko, M. d'Aquin, A. Togo +1
Machine learning promises to accelerate the material discovery by enabling high-throughput prediction of desirable macro-properties from atomic-level descriptors or structures. How…