53 citations · 119 across the 33 of their papers we have counts for
39 papers
inLoRA-MINT: Internal Representations for Auditing Training Data in Domain-adapted LLMs
Gonzalo Mancera, Julian Fierrez, Aythami Morales +3
This work investigates the application of the Membership Inference Test (MINT) to large language models (LLMs) fine-tuned with LoRA, aiming to determine whether specific samples we…
AICoFe Demo: AI-based Collaborative Feedback System
Alvaro Becerra, Alejandra Palma, Ruth Cobos +1
Peer feedback promotes active learning, critical reflection, and skill development, but its effectiveness is often limited by the quality of feedback students provide. Recent advan…
AISSA Demo: AI-based Student Slides Analysis Tool for Automated Grading and Feedback
Alvaro Becerra, Diego Gomez, Ruth Cobos +1
We present an AI-based web-oriented tool designed to support formative feedback for oral presentation slides in higher education: AISSA. It allows students to upload their slides b…
VideoRun2D Demo: Markerless Body Tracking for Biomechanical Analysis of Running
Luis F. Gomez, Julian Fierrez, Roberto Daza +5
Human pose estimation has advanced significantly due to the development of deep learning models, increased data availability, and improved computing resources. These developments h…
Mobile Interaction for Assessing Fatigue, Sleep, and Activity in Neurodegenerative and Chronic Diseases
Julian Fierrez, Alejandro Peña, Aythami Morales +13
Fatigue, sleep, or disturbances in daily activities are common symptoms among patients with neurodegenerative disorders (NDD) and immune-mediated inflammatory diseases (IMID). The…
FakeIDet3-DB: Refining Digital Attacks and Patch Extraction for Secure ID Benchmarking
Javier Muñoz-Haro, Muñoz-Haro Javier, Andres Teruel +11
Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI models can now inject localiz…
AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanations
Javier Irigoyen, Roberto Daza, Francisco Jurado +5
We present AIriskEval-edu Demo, a platform that audits the pedagogical quality of instructional explanations and provides explainable audit results. The platform evaluates an expla…
CrimeNER Demo: Named-Entity Recognition in the Crime Domain
Miguel Lopez-Duran, Julian Fierrez, Aythami Morales +7
We present CrimeNER Demo, an AI-powered platform that enables us to extract general crime-related information from documents and classify them into entity types with two levels of…
Unraveling Machine Behavior by Multi-Level Bias Analysis and Detection: Methodology and Application to Computer Vision
Ignacio Serna, Aythami Morales, Julian Fierrez
This study investigates the presence and propagation of bias within Neural Networks through a comprehensive multi-level analysis spanning the learned latent space, layer activation…
Comparative Study of Domain-adapted VLMs for General Document Visual Question Answering
Miguel Lopez-Duran, Elena Marrero, Julian Fierrez +8
Document Visual Question Answering (DocVQA) presents a complex multimodal challenge, requiring models to exploit visual, textual, and layout information from documents. Although Vi…
Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond
Javier Irigoyen, Roberto Daza, Aythami Morales +5
The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this impera…
AIriskEval-edu: New Dataset for Risk Assessment in AI-mediated K-12 Educational Explanations
Javier Irigoyen, Roberto Daza, Francisco Jurado +5
This work introduces AIriskEval-edu-db2, a new dataset designed to train and evaluate auditors based on LLMs for an explainable pedagogical risk assessment in instructional content…
Evaluating Social Engineering Risks in AI-based Interaction using Biometrics and a Gaming Setup
Roberto Daza, Javier Irigoyen, Ivan Lopez +5
We introduce AIriskEval-gaming, an open platform and dataset to evaluate social engineering risks in LLM-mediated multimodal interaction through controlled games. It supports human…
Is My Vision-Language Data in Your AI? Membership Inference Test (MINT) Demo 2
Daniel DeAlcala, Gonzalo Mancera, Julian Fierrez +3
We present the Membership Inference Test (MINT) Demo 2, a framework designed to improve transparency in machine learning training processes. MINT is a technique for experimentally…
Auditing Training Data in Domain-adapted LLMs: LoRA-MINT
Gonzalo Mancera, Daniel DeAlcala, Aythami Morales +3
We present LoRA-MINT, a new methodology for Membership Inference Test (MINT) applied to recent Large Language Models (LLMs) fine-tuned for specific Natural Language Processing (NLP…
Leveraging Avatar Fingerprinting: A Multi-Generator Photorealistic Talking-Head Public Database and Benchmark
Laura Pedrouzo-Rodriguez, Luis F. Gomez, Ruben Tolosana +4
Recent advances in photorealistic avatar generation have enabled highly realistic talking-head avatars, raising security concerns regarding identity impersonation in AI-mediated co…
Exploring Deep Learning and Ultra-Widefield Imaging for Diabetic Retinopathy and Macular Edema
Pablo Jimenez-Lizcano, Sergio Romero-Tapiador, Ruben Tolosana +4
Diabetic retinopathy (DR) and diabetic macular edema (DME) are leading causes of preventable blindness among working-age adults. Traditional approaches in the literature focus on s…
CrimeNER: Curated Dataset and Methods for Research and Investigation in Language Intelligence
Miguel Lopez-Duran, Julian Fierrez, Aythami Morales +7
The extraction of critical information from crime-related documents is a crucial task for law enforcement agencies. The extraction of this information can be interpreted as a Named…
Is It Really You? Exploring Biometric Verification Scenarios in Photorealistic Talking-Head Avatar Videos
Laura Pedrouzo-Rodriguez, Pedro Delgado-DeRobles, Luis F. Gomez +4
Photorealistic talking-head avatars are becoming increasingly common in virtual meetings, gaming, and social platforms. These avatars allow for more immersive communication, but th…
Are Vision-Language Models Ready for Dietary Assessment? Exploring the Next Frontier in AI-Powered Food Image Recognition
Sergio Romero-Tapiador, Ruben Tolosana, Blanca Lacruz-Pleguezuelos +7
Automatic dietary assessment based on food images remains a challenge, requiring precise food detection, segmentation, and classification. Vision-Language Models (VLMs) offer new p…
Personalized Weight Loss Management through Wearable Devices and Artificial Intelligence
Sergio Romero-Tapiador, Ruben Tolosana, Aythami Morales +10
Early detection of chronic and Non-Communicable Diseases (NCDs) is crucial for effective treatment during the initial stages. This study explores the application of wearable device…
VAAD: Visual Attention Analysis Dashboard applied to e-Learning
Miriam Navarro, Álvaro Becerra, Roberto Daza +3
In this paper, we present an approach in the Multimodal Learning Analytics field. Within this approach, we have developed a tool to visualize and analyze eye movement data collecte…
Biometrics and Behavior Analysis for Detecting Distractions in e-Learning
Álvaro Becerra, Javier Irigoyen, Roberto Daza +4
In this article, we explore computer vision approaches to detect abnormal head pose during e-learning sessions and we introduce a study on the effects of mobile phone usage during…
Privacy-Preserving Statistical Data Generation: Application to Sepsis Detection
Eric Macias-Fassio, Aythami Morales, Cristina Pruenza +1
The biomedical field is among the sectors most impacted by the increasing regulation of Artificial Intelligence (AI) and data protection legislation, given the sensitivity of patie…