no code implementations • 27 Sep 2023 • Valentin Barriere, Felipe del Rio, Andres Carvallo De Ferari, Carlos Aspillaga, Eugenio Herrera-Berg, Cristian Buc Calderon
Artificial neural networks typically struggle in generalizing to out-of-context examples.
1 code implementation • NAACL (BioNLP) 2021 • Vladimir Araujo, Andrés Carvallo, Carlos Aspillaga, Camilo Thorne, Denis Parra
The success of pretrained word embeddings has motivated their use in the biomedical domain, with contextualized embeddings yielding remarkable results in several biomedical NLP tasks.
no code implementations • Findings (ACL) 2021 • Carlos Aspillaga, Marcelo Mendoza, Alvaro Soto
The field of natural language understanding has experienced exponential progress in the last few years, with impressive results in several tasks.
no code implementations • 1 Jan 2021 • Carlos Aspillaga, Marcelo Mendoza, Alvaro Soto
The state of the art, previously dominated by pre-trained word embeddings, is now being pushed forward by large pre-trained contextual representation models.
no code implementations • 23 Apr 2020 • Vladimir Araujo, Andres Carvallo, Carlos Aspillaga, Denis Parra
We also show that we can significantly improve the robustness of the models by training them with adversarial examples.
no code implementations • LREC 2020 • Carlos Aspillaga, Andrés Carvallo, Vladimir Araujo
There has been significant progress in recent years in the field of Natural Language Processing thanks to the introduction of the Transformer architecture.
Natural Language Inference Natural Language Understanding +1