1 code implementation • 3 Dec 2023 • Andrés Villa, Juan Carlos León Alcázar, Alvaro Soto, Bernard Ghanem
This paper introduces a Multi-modal Evaluation Benchmark named MERLIM, a scalable test-bed to assess the performance of IT-LVLMs on fundamental computer vision tasks.
no code implementations • CVPR 2023 • Andrés Villa, Juan León Alcázar, Motasem Alfarra, Kumail Alhamoud, Julio Hurtado, Fabian Caba Heilbron, Alvaro Soto, Bernard Ghanem
In this paper, we address the problem of continual learning for video data.
no code implementations • CVPR 2022 • Andrés Villa, Kumail Alhamoud, Juan León Alcázar, Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem
We perform in-depth evaluations of existing CL methods in vCLIMB, and observe two unique challenges in video data.
no code implementations • EMNLP 2021 • Vladimir Araujo, Andrés Villa, Marcelo Mendoza, Marie-Francine Moens, Alvaro Soto
Current language models are usually trained using a self-supervised scheme, where the main focus is learning representations at the word or sentence level.
2 code implementations • 21 Jun 2021 • Andrés Villa, Juan-Manuel Perez-Rua, Vladimir Araujo, Juan Carlos Niebles, Victor Escorcia, Alvaro Soto
Recently, few-shot learning has received increasing interest.
1 code implementation • 30 Jul 2020 • Andrés Villa, Vladimir Araujo, Francisca Cattan, Denis Parra
Our evaluation indicates that both the Transformer architecture and the contextual information are essential to get the best results for this item recommendation task.