2 citations · 3 across the 4 of their papers we have counts for
4 papers
A Domain-Based Taxonomy of Jailbreak Vulnerabilities in Large Language Models
Carlos Peláez-González, Andrés Herrera-Poyatos, Cristina Zuheros +3
The study of large language models (LLMs) is a key area in open-world machine learning. Although LLMs demonstrate remarkable natural language processing capabilities, they also fac…
An overview of model uncertainty and variability in LLM-based sentiment analysis. Challenges, mitigation strategies and the role of explainability
David Herrera-Poyatos, Carlos Peláez-González, Cristina Zuheros +4
Large Language Models (LLMs) have significantly advanced sentiment analysis, yet their inherent uncertainty and variability pose critical challenges to achieving reliable and consi…
The H-Elena Trojan Virus to Infect Model Weights: A Wake-Up Call on the Security Risks of Malicious Fine-Tuning
Virilo Tejedor, Cristina Zuheros, Carlos Peláez-González +3
Large Language Models (LLMs) offer powerful capabilities in text generation and are increasingly adopted across a wide range of domains. However, their open accessibility and fine-…
Deep Learning methodology for the identification of wood species using high-resolution macroscopic images
David Herrera-Poyatos, Andrés Herrera-Poyatos, Rosana Montes +5
Significant advancements in the field of wood species identification are needed worldwide to support sustainable timber trade. In this work we contribute to automate the identifica…