collaborators

7 papers

cs.MA2026

Holonic Active Distillation for Scalable Multi-Agent Learning in Multi-Sensor Systems

Dani Manjah, Tim Bary, Benoît Macq +1

The rapid expansion of sensor-based networks introduces major challenges in scalability, adaptability, and knowledge transfer, especially in open environments where new subsystems…

cs.CV2026

Localized Conformal Prediction for Image Classification with Vision-Language Models

Clément Fuchs, Tim Bary, Benoît Macq

Conformal predictions have attracted significant attention in the field of uncertainty quantification, mainly because of their strong marginal coverage guarantees. Full conditional…

cs.CV2026

CADS: Conformal Adaptive Decision System for Cost-Efficient Image Classification

Mikael Turkoglu, Tim Bary, Vincent Thielens +2

While high-capacity AI models have advanced state-of-the-art performance, their practical deployment is often hindered by high inference costs, environmental impact, and a "one-siz…

cs.LG2026

No Need for Learning to Defer? A Training Free Deferral Framework to Multiple Experts through Conformal Prediction

Tim Bary, Benoît Macq, Louis Petit

AI systems often struggle to provide reliable predictions across all inputs, motivating hybrid human-AI decision-making. Existing Learning to Defer (L2D) approaches address this by…

cs.LG2025

Optimizing Resources for On-the-Fly Label Estimation with Multiple Unknown Medical Experts

Tim Bary, Tiffanie Godelaine, Axel Abels +1

Accurate ground truth estimation in medical screening programs often relies on coalitions of experts and peer second opinions. Algorithms that efficiently aggregate noisy annotatio…

cs.CV2025

Data-Efficient Stream-Based Active Distillation for Scalable Edge Model Deployment

Dani Manjah, Tim Bary, Benoît Gérin +2

Edge camera-based systems are continuously expanding, facing ever-evolving environments that require regular model updates. In practice, complex teacher models are run on a central…