19 citations · 23 across the 10 of their papers we have counts for
11 papers
What Human-AI Interaction Leaves Behind: Residual Human States -- A Trajectory-Based Framework and Multi-Study Analysis
David Herrera-Poyatos, Carlos Peláez-González, Cristina Zuheros +1
Human-AI Interaction is commonly evaluated by what an artificial agent enables during use, yet interaction can also alter the human who acts next. We introduce Residual Human State…
Triadic Fusion of Cognitive, Functional, and Causal Dimensions for Explainable LLMs: The TAXAL Framework
David Herrera-Poyatos, Carlos Peláez-González, Cristina Zuheros +3
Large Language Models (LLMs) are increasingly being deployed in high-risk domains where opacity, bias, and instability undermine trust and accountability. Traditional explainabilit…
An Online A/B Testing Decision Support System for Web Usability Assessment Based on a Linguistic Decision-making Methodology: Case of Study a Virtual Learning Environment
Noe Zermeño, Cristina Zuheros, Lucas Daniel Del Rosso Calache +2
In recent years, attention has increasingly focused on enhancing user satisfaction with user interfaces, spanning both mobile applications and websites. One fundamental aspect of h…
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-…
FLEX: FLEXible Federated Learning Framework
Francisco Herrera, Daniel Jiménez-López, Alberto Argente-Garrido +6
In the realm of Artificial Intelligence (AI), the need for privacy and security in data processing has become paramount. As AI applications continue to expand, the collection and h…
An Interpretable Client Decision Tree Aggregation process for Federated Learning
Alberto Argente-Garrido, Cristina Zuheros, M. Victoria Luzón +1
Trustworthy Artificial Intelligence solutions are essential in today's data-driven applications, prioritizing principles such as robustness, safety, transparency, explainability, a…
Large language models for crowd decision making based on prompt design strategies using ChatGPT: models, analysis and challenges
David Herrera-Poyatos, Cristina Zuheros, Rosana Montes +1
Social Media and Internet have the potential to be exploited as a source of opinion to enrich Decision Making solutions. Crowd Decision Making (CDM) is a methodology able to infer…
Design and consensus content validity of the questionnaire for b-learning education: A 2-Tuple Fuzzy Linguistic Delphi based Decision Support Tool
Rosana Montes, Cristina Zuheros, Jeovani M. Morales +3
Classic Delphi and Fuzzy Delphi methods are used to test content validity of data collection tools such as questionnaires. Fuzzy Delphi takes the opinion issued by judges from a li…
Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology using Natural Language Processing and Deep Learning for Smarter Decision Aid. Case study of restaurant choice using TripAdvisor reviews
Cristina Zuheros, Eugenio Martínez-Cámara, Enrique Herrera-Viedma +1
Decision making models are constrained by taking the expert evaluations with pre-defined numerical or linguistic terms. We claim that the use of sentiment analysis will allow decis…