1 code implementation • SemEval (NAACL) 2022 • Álvaro Huertas-García, Helena Liz, Guillermo Villar-Rodríguez, Alejandro Martín, Javier Huertas-Tato, David Camacho
The main contribution of this paper is the exploration of different late fusion methods to boost the performance of the combination based on the Transformer-based model and Convolutional Neural Networks (CNN) for text and image, respectively.
no code implementations • 15 Feb 2024 • Álvaro Huertas-García, Alejandro Martín, Javier Huertas-Tato, David Camacho
This approach effectively reduces the performance drop in encoder-only models to an average of 5% in offensive language detection and 2% in misinformation detection tasks.
1 code implementation • 17 Oct 2023 • Javier Huertas-Tato, Alejandro Martin, David Camacho
Additionally, we attain promising results on PAN verification challenges using a single dense layer, with our model serving as an embedding encoder.
no code implementations • 8 Jun 2023 • Helena Liz-López, Javier Huertas-Tato, Jorge Pérez-Aracil, Carlos Casanova-Mateo, Julia Sanz-Justo, David Camacho
Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems.
1 code implementation • 30 Sep 2022 • Javier Huertas-Tato, Alvaro Huertas-Garcia, Alejandro Martin, David Camacho
The model is evaluated on these datasets, achieving zero-shot 72. 39\% and 86. 73\% accuracy and top-5 accuracy respectively on the joint evaluation dataset when determining authorship from a set of 250 different authors.
no code implementations • 28 Jul 2022 • Helena Liz, Javier Huertas-Tato, Manuel Sánchez-Montañés, Javier Del Ser, David Camacho
To apply these algorithms in different fields and test how the methodology works, we need to use eXplainable AI techniques.
no code implementations • 18 Apr 2022 • Álvaro Huertas-García, Alejandro Martín, Javier Huertas-Tato, David Camacho
The results of this study will significantly contribute to the understanding of how different tuning approaches affect performance on semantic-aware tasks and how dimensional reduction techniques deal with the high-dimensional embeddings computed for the STS task and their potential for highly demanding NLP tasks
no code implementations • 7 Apr 2022 • Javier Huertas-Tato, Alejandro Martin, David Camacho
Our motivation is to provide a powerful resource to better understand Spanish Twitter and to be used on applications focused on this social network, with special emphasis on solutions devoted to tackle the spreading of misinformation in this platform.
no code implementations • 27 Oct 2021 • Alejandro Martín, Javier Huertas-Tato, Álvaro Huertas-García, Guillermo Villar-Rodríguez, David Camacho
Our society produces and shares overwhelming amounts of information through Online Social Networks (OSNs).
no code implementations • 17 Mar 2021 • Javier Huertas-Tato, Alejandro Martín, David Camacho
In this paper, we propose a new architecture called Siamese Inter-Lingual Transformer (SILT), to efficiently align multilingual embeddings for Natural Language Inference, allowing for unmatched language pairs to be processed.
1 code implementation • 20 Dec 2020 • Javier Huertas-Tato, Alejandro Martín, Julián Fierrez, David Camacho
In this paper, an ensemble method is proposed for accurate image classification, fusing automatically detected features through Convolutional Neural Network architectures with a set of manually defined statistical indicators.