activity
20212026
most citedA distillation-based approach integrating continual learning and federated learning for pervasive services

33 citations · 34 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Appraisal Dimensions Generalise Better than Emotion Labels for Cross-Age Affect Recognition in AI-Assisted Healthcare

Hippolyte Fournier, Safaa Azzakhnini, Sina Alisamir +14

The integration of artificial intelligence (AI) into healthcare has advanced significantly, yet affect recognition remains a major challenge, particularly in AI-assisted interventi…

cs.CL2026

What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search

Xinhao Zhang, Xi Chen, François Portet +1

Recent work has demonstrated the promise of orchestrating large language models (LLMs) within evolutionary and agentic optimization systems. However, the mechanisms driving these o…

cs.CL2026

Pantagruel: Unified Self-Supervised Encoders for French Text and Speech

Phuong-Hang Le, Valentin Pelloin, Arnault Chatelain +27

We release Pantagruel models, a new family of self-supervised encoder models for French text and speech. Instead of predicting modality-tailored targets such as textual tokens or s…

cs.LG2024★ 1 cited

FedAli: Personalized Federated Learning Alignment with Prototype Layers for Generalized Mobile Services

Sannara Ek, Kaile Wang, François Portet +2

Personalized Federated Learning (PFL) enables distributed training on edge devices, allowing models to collaboratively learn global patterns while tailoring their parameters to bet…

cs.AI2021★ 33 cited

A distillation-based approach integrating continual learning and federated learning for pervasive services

Anastasiia Usmanova, François Portet, Philippe Lalanda +1

Federated Learning, a new machine learning paradigm enhancing the use of edge devices, is receiving a lot of attention in the pervasive community to support the development of smar…