7 citations · 11 across the 5 of their papers we have counts for
6 papers
Language Models Can Explain Visual Features via Steering
Javier Ferrando, Enrique Lopez-Cuena, Pablo Agustin Martin-Torres +3
Sparse Autoencoders uncover thousands of features in vision models, yet explaining these features without requiring human intervention remains an open challenge. While previous wor…
The Aloe Family Recipe for Open and Specialized Healthcare LLMs
Dario Garcia-Gasulla, Jordi Bayarri-Planas, Ashwin Kumar Gururajan +10
Purpose: With advancements in Large Language Models (LLMs) for healthcare, the need arises for competitive open-source models to protect the public interest. This work contributes…
Automatic Evaluation of Healthcare LLMs Beyond Question-Answering
Anna Arias-Duart, Pablo Agustin Martin-Torres, Daniel Hinjos +7
Current Large Language Models (LLMs) benchmarks are often based on open-ended or close-ended QA evaluations, avoiding the requirement of human labor. Close-ended measurements evalu…
Aloe: A Family of Fine-tuned Open Healthcare LLMs
Ashwin Kumar Gururajan, Enrique Lopez-Cuena, Jordi Bayarri-Planas +10
As the capabilities of Large Language Models (LLMs) in healthcare and medicine continue to advance, there is a growing need for competitive open-source models that can safeguard pu…
Padding Aware Neurons
Dario Garcia-Gasulla, Victor Gimenez-Abalos, Pablo Martin-Torres
Convolutional layers are a fundamental component of most image-related models. These layers often implement by default a static padding policy (\eg zero padding), to control the sc…
Exploring the Role of Explainability in AI-Assisted Embryo Selection
Lucia Urcelay, Daniel Hinjos, Pablo A. Martin-Torres +5
In Vitro Fertilization is among the most widespread treatments for infertility. One of its main challenges is the evaluation and selection of embryo for implantation, a process wit…