Search Results for author: Jordi Armengol-Estapé

Found 17 papers, 12 papers with code

Pretrained Biomedical Language Models for Clinical NLP in Spanish

1 code implementation BioNLP (ACL) 2022 Casimiro Pio Carrino, Joan Llop, Marc Pàmies, Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Joaquín Silveira-Ocampo, Alfonso Valencia, Aitor Gonzalez-Agirre, Marta Villegas

This work presents the first large-scale biomedical Spanish language models trained from scratch, using large biomedical corpora consisting of a total of 1. 1B tokens and an EHR corpus of 95M tokens.


Sequence-to-Sequence Resources for Catalan

1 code implementation14 Feb 2022 Ona de Gibert, Ksenia Kharitonova, Blanca Calvo Figueras, Jordi Armengol-Estapé, Maite Melero

In this work, we introduce sequence-to-sequence language resources for Catalan, a moderately under-resourced language, towards two tasks, namely: Summarization and Machine Translation (MT).

Abstractive Text Summarization Machine Translation +1

FinEAS: Financial Embedding Analysis of Sentiment

1 code implementation31 Oct 2021 Asier Gutiérrez-Fandiño, Miquel Noguer i Alonso, Petter Kolm, Jordi Armengol-Estapé

We introduce a new language representation model in finance called Financial Embedding Analysis of Sentiment (FinEAS).

Sentence Embeddings Sentiment Analysis +2

Spanish Legalese Language Model and Corpora

1 code implementation23 Oct 2021 Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Aitor Gonzalez-Agirre, Marta Villegas

There are many Language Models for the English language according to its worldwide relevance.

Language Modelling

Spanish Biomedical Crawled Corpus: A Large, Diverse Dataset for Spanish Biomedical Language Models

no code implementations16 Sep 2021 Casimiro Pio Carrino, Jordi Armengol-Estapé, Ona de Gibert Bonet, Asier Gutiérrez-Fandiño, Aitor Gonzalez-Agirre, Martin Krallinger, Marta Villegas

We introduce CoWeSe (the Corpus Web Salud Espa\~nol), the largest Spanish biomedical corpus to date, consisting of 4. 5GB (about 750M tokens) of clean plain text.

Biomedical and Clinical Language Models for Spanish: On the Benefits of Domain-Specific Pretraining in a Mid-Resource Scenario

no code implementations8 Sep 2021 Casimiro Pio Carrino, Jordi Armengol-Estapé, Asier Gutiérrez-Fandiño, Joan Llop-Palao, Marc Pàmies, Aitor Gonzalez-Agirre, Marta Villegas

To the best of our knowledge, we provide the first biomedical and clinical transformer-based pretrained language models for Spanish, intending to boost native Spanish NLP applications in biomedicine.

Named Entity Recognition NER +1

On the Multilingual Capabilities of Very Large-Scale English Language Models

1 code implementation30 Aug 2021 Jordi Armengol-Estapé, Ona de Gibert Bonet, Maite Melero

Generative Pre-trained Transformers (GPTs) have recently been scaled to unprecedented sizes in the history of machine learning.

Few-Shot Learning Language Modelling +2

Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan

no code implementations Findings (ACL) 2021 Jordi Armengol-Estapé, Casimiro Pio Carrino, Carlos Rodriguez-Penagos, Ona de Gibert Bonet, Carme Armentano-Oller, Aitor Gonzalez-Agirre, Maite Melero, Marta Villegas

For this, we: (1) build a clean, high-quality textual Catalan corpus (CaText), the largest to date (but only a fraction of the usual size of the previous work in monolingual language models), (2) train a Transformer-based language model for Catalan (BERTa), and (3) devise a thorough evaluation in a diversity of settings, comprising a complete array of downstream tasks, namely, Part of Speech Tagging, Named Entity Recognition and Classification, Text Classification, Question Answering, and Semantic Textual Similarity, with most of the corresponding datasets being created ex novo.

Language Modelling Named Entity Recognition +4

Characterizing and Measuring the Similarity of Neural Networks with Persistent Homology

1 code implementation NeurIPS 2021 David Pérez-Fernández, Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Marta Villegas

Characterizing the structural properties of neural networks is crucial yet poorly understood, and there are no well-established similarity measures between networks.

Topological Data Analysis

A Vulnerability Study on Academic Collaboration Networks Based on Network Dynamics

1 code implementation21 Dec 2020 Asier Gutiérrez-Fandiño, Jordi Armengol-Estapé, Marta Villegas

Email can be one of the most fruitful attack vectors of research institutions as they also contain access to all accounts and thus to all private information.

Cryptography and Security Social and Information Networks

Enriching the Transformer with Linguistic Factors for Low-Resource Machine Translation

no code implementations RANLP 2021 Jordi Armengol-Estapé, Marta R. Costa-jussà, Carlos Escolano

Introducing factors, that is to say, word features such as linguistic information referring to the source tokens, is known to improve the results of neural machine translation systems in certain settings, typically in recurrent architectures.

Machine Translation Translation

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