16 papers
DynaMiCS: Fine-tuning LLMs with Performance Constraints using Dynamic Mixtures
Eleonora Gualdoni, Sonia Laguna, Louis Bethune +3
Multi-domain fine-tuning of large language models requires improving performance on target domains while preserving performance on constrained domains, such as general knowledge, i…
Foundation Model for Cardiac Time Series via Masked Latent Attention
Moritz Vandenhirtz, Samuel Ruipérez-Campillo, Simon Böhi +6
Electrocardiograms (ECGs) are among the most widely available clinical signals and play a central role in cardiovascular diagnosis. While recent foundation models (FMs) have shown…
Beyond Independent Frames: Latent Attention Masked Autoencoders for Multi-View Echocardiography
Simon Böhi, Irene Cannistraci, Sergio Muñoz Gonzalez +8
Echocardiography is a widely used modality for cardiac assessment due to its non-invasive and cost-effective nature, but the sparse and heterogeneous spatiotemporal views of the he…
Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion
Sonia Laguna, Jorge da Silva Goncalves, Moritz Vandenhirtz +3
Machine unlearning is rapidly becoming a practical requirement, driven by privacy regulations, data errors, and the need to remove harmful or corrupted training samples. Despite th…
Structure is Supervision: Multiview Masked Autoencoders for Radiology
Sonia Laguna, Andrea Agostini, Alain Ryser +9
Building robust medical machine learning systems requires pretraining strategies that exploit the intrinsic structure present in clinical data. We introduce Multiview Masked Autoen…
Steering Generative Models for Accessibility: EasyRead Image Generation
Nicolas Dickenmann, Yanis Merzouki, Sonia Laguna +4
EasyRead pictograms are simple, visually clear images that represent specific concepts and support comprehension for people with intellectual disabilities, low literacy, or languag…