7 citations · 10 across the 5 of their papers we have counts for
6 papers
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…
Efficient Safety Retrofitting Against Jailbreaking for LLMs
Dario Garcia-Gasulla, Adrian Tormos, Anna Arias-Duart +4
Direct Preference Optimization (DPO) is an efficient alignment technique that steers LLMs towards preferable outputs by training on preference data, bypassing the need for explicit…
Data Augmentation with Diffusion Models for Colon Polyp Localization on the Low Data Regime: How much real data is enough?
Adrian Tormos, Blanca Llauradó, Fernando Núñez +3
The scarcity of data in medical domains hinders the performance of Deep Learning models. Data augmentation techniques can alleviate that problem, but they usually rely on functiona…
Intention-aware policy graphs: answering what, how, and why in opaque agents
Victor Gimenez-Abalos, Sergio Alvarez-Napagao, Adrian Tormos +2
Agents are a special kind of AI-based software in that they interact in complex environments and have increased potential for emergent behaviour. Explaining such emergent behaviour…
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…
When & How to Transfer with Transfer Learning
Adrian Tormos, Dario Garcia-Gasulla, Victor Gimenez-Abalos +1
In deep learning, transfer learning (TL) has become the de facto approach when dealing with image related tasks. Visual features learnt for one task have been shown to be reusable…