most citedA Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages

75 citations · 89 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL202075 cited

A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages

Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot

We use the multilingual OSCAR corpus, extracted from Common Crawl via language classification, filtering and cleaning, to train monolingual contextualized word embeddings (ELMo) fo…

cs.CL20203 cited

Establishing a New State-of-the-Art for French Named Entity Recognition

Pedro Javier Ortiz Suárez, Yoann Dupont, Benjamin Muller +2

The French TreeBank developed at the University Paris 7 is the main source of morphosyntactic and syntactic annotations for French. However, it does not include explicit informatio…

cs.CL20203 cited

ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations

Fernando Alva-Manchego, Louis Martin, Antoine Bordes +3

In order to simplify a sentence, human editors perform multiple rewriting transformations: they split it into several shorter sentences, paraphrase words (i.e. replacing complex wo…

cs.CL20208 cited

Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi

Benjamin Muller, Benoit Sagot, Djamé Seddah

Building natural language processing systems for non standardized and low resource languages is a difficult challenge. The recent success of large-scale multilingual pretrained lan…

cs.CL2019

CamemBERT: a Tasty French Language Model

Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez +5

Pretrained language models are now ubiquitous in Natural Language Processing. Despite their success, most available models have either been trained on English data or on the concat…

cs.CL2019

Controllable Sentence Simplification

Louis Martin, Benoît Sagot, Éric de la Clergerie +1

Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical. It is often conside…