Search Results for author:
Found 8 papers, 2 papers with code
Predicting affinity ties in a surname network
From administrative registers of last names in Santiago, Chile, we create a surname affinity network that encodes socioeconomic data.
Evaluation Benchmarks for Spanish Sentence Representations
Due to the success of pre-trained language models, versions of languages other than English have been released in recent years.
Augmenting BERT-style Models with Predictive Coding to Improve Discourse-level Representations
Current language models are usually trained using a self-supervised scheme, where the main focus is learning representations at the word or sentence level.
Neural Abstractive Unsupervised Summarization of Online News Discussions
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
Inspecting the concept knowledge graph encoded by modern language models
The field of natural language understanding has experienced exponential progress in the last few years, with impressive results in several tasks.
A data-driven strategy to combine word embeddings in information retrieval
We use Idf combinations of embeddings to represent queries, showing that these representations outperform the average word embeddings recently proposed in the literature.
Tracking the progress of Language Models by extracting their underlying Knowledge Graphs
The state of the art, previously dominated by pre-trained word embeddings, is now being pushed forward by large pre-trained contextual representation models.
Says who? Automatic Text-Based Content Analysis of Television News
We perform an automatic analysis of television news programs, based on the closed captions that accompany them.
