no code implementations • 2 Jun 2023 • Marcelo Mendoza, Naim Bro
From administrative registers of last names in Santiago, Chile, we create a surname affinity network that encodes socioeconomic data.
1 code implementation • LREC 2022 • Vladimir Araujo, Andrés Carvallo, Souvik Kundu, José Cañete, Marcelo Mendoza, Robert E. Mercer, Felipe Bravo-Marquez, Marie-Francine Moens, Alvaro Soto
Due to the success of pre-trained language models, versions of languages other than English have been released in recent years.
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.
1 code implementation • 7 Jun 2021 • Ignacio Tampe Palma, Marcelo Mendoza, Evangelos Milios
Our novel approach provides a summary that represents the most relevant aspects of a news item that users comment on, incorporating the social context as a source of information to summarize texts in online social networks.
Abstractive Text Summarization Unsupervised Text Summarization
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 • 26 May 2021 • Alfredo Silva, Marcelo Mendoza
We use Idf combinations of embeddings to represent queries, showing that these representations outperform the average word embeddings recently proposed in the literature.
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 • 18 Jul 2013 • Carlos Castillo, Gianmarco De Francisci Morales, Marcelo Mendoza, Nasir Khan
We perform an automatic analysis of television news programs, based on the closed captions that accompany them.