52 citations · 67 across the 9 of their papers we have counts for
5 papers · 1 filter
A Framework for Using LLMs for Repository Mining Studies in Empirical Software Engineering
Vincenzo de Martino, Joel Castaño, Fabio Palomba +2
Context: The emergence of Large Language Models (LLMs) has significantly transformed Software Engineering (SE) by providing innovative methods for analyzing software repositories.…
How do Machine Learning Models Change?
Joel Castaño, Rafael Cabañas, Antonio Salmerón +2
The proliferation of Machine Learning (ML) models and their open-source implementations has transformed Artificial Intelligence research and applications. Platforms like Hugging Fa…
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models
Alexandra González Álvarez, Joel Castaño, Xavier Franch +1
Background: Given the fast-paced nature of today's technology, which has surpassed human performance in tasks like image classification, visual reasoning, and English understanding…
Lessons Learned from Mining the Hugging Face Repository
Joel Castaño, Silverio Martínez-Fernández, Xavier Franch
The rapidly evolving fields of Machine Learning (ML) and Artificial Intelligence have witnessed the emergence of platforms like Hugging Face (HF) as central hubs for model developm…
GAISSALabel: A tool for energy labeling of ML models
Pau Duran, Joel Castaño, Cristina Gómez +1
Background: The increasing environmental impact of Information Technologies, particularly in Machine Learning (ML), highlights the need for sustainable practices in software engine…