activity
20202025
most citedExploring Dimensionality Reduction Techniques in Multilingual Transformers

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2025

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…

cs.MM2024

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…

cs.CL20221 cited

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…

cs.CL2021

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…

cs.CV2020

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…