4 citations · 18 across the 20 of their papers we have counts for
22 papers
Behind the Mask: A Taxonomic Analysis of Activities in Online Social Networks
Debora F De Souza, Gabriela Beltrao, Berta Chulvi +12
The broadcast of disinformation in online social networks (OSN) is a growing concern examined across several disciplines, including human-computer interaction (HCI). The pervasive…
xList-Hate: A Checklist-Based Framework for Interpretable and Generalizable Hate Speech Detection
Adrián Girón, Pablo Miralles, Javier Huertas-Tato +2
Hate speech detection is commonly framed as a direct binary classification problem despite being a composite concept defined through multiple interacting factors that vary across l…
Supervised Contrastive Learning for Few-Shot AI-Generated Image Detection and Attribution
Jaime Álvarez Urueña, David Camacho, Javier Huertas Tato
The rapid advancement of generative artificial intelligence has enabled the creation of synthetic images that are increasingly indistinguishable from authentic content, posing sign…
One-shot Style Transfer LLM log-probabilities for Authorship Attribution and Verification
Pablo Miralles-González, Javier Huertas-Tato, Alejandro Martín +1
Computational stylometry studies writing style through quantitative textual patterns, enabling applications such as authorship attribution, identity linking, and plagiarism detecti…
Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics
Inmaculada Santamaria-Valenzuela, Victor Rodriguez-Fernandez, Javier Huertas-Tato +2
The present study explores the interpretability of latent spaces produced by time series foundation models, focusing on their potential for visual analysis tasks. Specifically, we…
Evaluating the Scalability and Adversarial Generalization of GRPO-Trained NLI Models
Pablo Miralles-González, Javier Huertas-Tato, Alejandro Martín +1
Natural Language Inference (NLI) is a central task in natural language understanding with applications in fact-checking, question answering, and information retrieval. Despite its…
On the locality bias and results in the Long Range Arena
Pablo Miralles-González, Javier Huertas-Tato, Alejandro Martín +1
The Long Range Arena (LRA) benchmark was designed to evaluate the performance of Transformer improvements and alternatives in long-range dependency modeling tasks. The Transformer…
Not all tokens are created equal: Perplexity Attention Weighted Networks for AI generated text detection
Pablo Miralles-González, Javier Huertas-Tato, Alejandro Martín +1
The rapid advancement in large language models (LLMs) has significantly enhanced their ability to generate coherent and contextually relevant text, raising concerns about the misus…
Isolating authorship from content with semantic embeddings and contrastive learning
Javier Huertas-Tato, Adrián Girón-Jiménez, Alejandro Martín +1
Authorship has entangled style and content inside. Authors frequently write about the same topics in the same style, so when different authors write about the exact same topic the…
A CLIP-based siamese approach for meme classification
Javier Huertas-Tato, Christos Koutlis, Symeon Papadopoulos +2
Memes are an increasingly prevalent element of online discourse in social networks, especially among young audiences. They carry ideas and messages that range from humorous to hate…
DisTrack: a new Tool for Semi-automatic Misinformation Tracking in Online Social Networks
Guillermo Villar-Rodríguez, Álvaro Huertas-García, Alejandro Martín +2
Introduction: This article introduces DisTrack, a methodology and a tool developed for tracking and analyzing misinformation within Online Social Networks (OSNs). DisTrack is desig…
Camouflage is all you need: Evaluating and Enhancing Language Model Robustness Against Camouflage Adversarial Attacks
Álvaro Huertas-García, Alejandro Martín, Javier Huertas-Tato +1
Adversarial attacks represent a substantial challenge in Natural Language Processing (NLP). This study undertakes a systematic exploration of this challenge in two distinct phases:…
Understanding writing style in social media with a supervised contrastively pre-trained transformer
Javier Huertas-Tato, Alejandro Martin, David Camacho
Online Social Networks serve as fertile ground for harmful behavior, ranging from hate speech to the dissemination of disinformation. Malicious actors now have unprecedented freedo…
Spain on Fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information
Helena Liz-López, Javier Huertas-Tato, Jorge Pérez-Aracil +3
Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems. Humans cause 90% of them (negligence or provoked) and the behaviour of individuals is unpredict…
Countering Malicious Content Moderation Evasion in Online Social Networks: Simulation and Detection of Word Camouflage
Álvaro Huertas-García, Alejandro Martín, Javier Huertas Tato +1
Content moderation is the process of screening and monitoring user-generated content online. It plays a crucial role in stopping content resulting from unacceptable behaviors such…
PART: Pre-trained Authorship Representation Transformer
Javier Huertas-Tato, Alejandro Martin, David Camacho
Authors writing documents imprint identifying information within their texts: vocabulary, registry, punctuation, misspellings, or even emoji usage. Previous works use hand-crafted…
Deep learning for understanding multilabel imbalanced Chest X-ray datasets
Helena Liz, Javier Huertas-Tato, Manuel Sánchez-Montañés +2
Over the last few years, convolutional neural networks (CNNs) have dominated the field of computer vision thanks to their ability to extract features and their outstanding performa…
Exploring Dimensionality Reduction Techniques in Multilingual Transformers
Álvaro Huertas-García, Alejandro Martín, Javier Huertas-Tato +1
Both in scientific literature and in industry,, Semantic and context-aware Natural Language Processing-based solutions have been gaining importance in recent years. The possibiliti…
BERTuit: Understanding Spanish language in Twitter through a native transformer
Javier Huertas-Tato, Alejandro Martin, David Camacho
The appearance of complex attention-based language models such as BERT, Roberta or GPT-3 has allowed to address highly complex tasks in a plethora of scenarios. However, when appli…
FacTeR-Check: Semi-automated fact-checking through Semantic Similarity and Natural Language Inference
Alejandro Martín, Javier Huertas-Tato, Álvaro Huertas-García +2
Our society produces and shares overwhelming amounts of information through Online Social Networks (OSNs). Within this environment, misinformation and disinformation have prolifera…
SILT: Efficient transformer training for inter-lingual inference
Javier Huertas-Tato, Alejandro Martín, David Camacho
The ability of transformers to perform precision tasks such as question answering, Natural Language Inference (NLI) or summarising, have enabled them to be ranked as one of the bes…
Fusing CNNs and statistical indicators to improve image classification
Javier Huertas-Tato, Alejandro Martín, Julián Fierrez +1
Convolutional Networks have dominated the field of computer vision for the last ten years, exhibiting extremely powerful feature extraction capabilities and outstanding classificat…