4 citations · 4 across the 5 of their papers we have counts for
6 papers
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…
Post-hoc Stochastic Concept Bottleneck Models
Wiktor Jan Hoffmann, Sonia Laguna, Moritz Vandenhirtz +2
Concept Bottleneck Models (CBMs) are interpretable models that predict the target variable through high-level human-understandable concepts, allowing users to intervene on mispredi…
From Logits to Hierarchies: Hierarchical Clustering made Simple
Emanuele Palumbo, Moritz Vandenhirtz, Alain Ryser +2
The hierarchical structure inherent in many real-world datasets makes the modeling of such hierarchies a crucial objective in both unsupervised and supervised machine learning. Whi…
TOAST: Transformer Optimization using Adaptive and Simple Transformations
Irene Cannistraci, Simone Antonelli, Emanuele Palumbo +4
Foundation models achieve state-of-the-art performance across different tasks, but their size and computational demands raise concerns about accessibility and sustainability. Exist…
Identifiability Results for Multimodal Contrastive Learning
Imant Daunhawer, Alice Bizeul, Emanuele Palumbo +2
Contrastive learning is a cornerstone underlying recent progress in multi-view and multimodal learning, e.g., in representation learning with image/caption pairs. While its effecti…
On the Limitations of Multimodal VAEs
Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong +2
Multimodal variational autoencoders (VAEs) have shown promise as efficient generative models for weakly-supervised data. Yet, despite their advantage of weak supervision, they exhi…