Search Results for author: Louis Martin

Found 10 papers, 7 papers with code

Rethinking Automatic Evaluation in Sentence Simplification

2 code implementations15 Apr 2021 Thomas Scialom, Louis Martin, Jacopo Staiano, Éric Villemonte de la Clergerie, Benoît Sagot

In the context of Sentence Simplification, this is particularly challenging: the task requires by nature to replace complex words with simpler ones that shares the same meaning.

Machine Translation Text Generation

Les mod\`eles de langue contextuels Camembert pour le fran\ccais : impact de la taille et de l'h\'et\'erog\'en\'eit\'e des donn\'ees d'entrainement (C AMEM BERT Contextual Language Models for French: Impact of Training Data Size and Heterogeneity )

no code implementations JEPTALNRECITAL 2020 Louis Martin, Benjamin Muller, Pedro Javier Ortiz Su{\'a}rez, Yoann Dupont, Laurent Romary, {\'E}ric Villemonte de la Clergerie, Beno{\^\i}t Sagot, Djam{\'e} Seddah

L{'}utilisation pratique de ces mod{\`e}les {---} dans toutes les langues sauf l{'}anglais {---} {\'e}tait donc limit{\'e}e. La sortie r{\'e}cente de plusieurs mod{\`e}les monolingues fond{\'e}s sur BERT (Devlin et al., 2019), notamment pour le fran{\c{c}}ais, a d{\'e}montr{\'e} l{'}int{\'e}r{\^e}t de ces mod{\`e}les en am{\'e}liorant l{'}{\'e}tat de l{'}art pour toutes les t{\^a}ches {\'e}valu{\'e}es.


MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases

1 code implementation1 May 2020 Louis Martin, Angela Fan, Éric de la Clergerie, Antoine Bordes, Benoît Sagot

Progress in sentence simplification has been hindered by a lack of labeled parallel simplification data, particularly in languages other than English.

Parallel Corpus Mining Text Simplification

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

1 code implementation ACL 2020 Fernando Alva-Manchego, Louis Martin, Antoine Bordes, Carolina Scarton, Benoît Sagot, Lucia Specia

Furthermore, we motivate the need for developing better methods for automatic evaluation using ASSET, since we show that current popular metrics may not be suitable when multiple simplification transformations are performed.

Controllable Sentence Simplification

2 code implementations LREC 2020 Louis Martin, Benoît Sagot, Éric de la Clergerie, Antoine Bordes

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

Text Simplification

EASSE: Easier Automatic Sentence Simplification Evaluation

1 code implementation IJCNLP 2019 Fernando Alva-Manchego, Louis Martin, Carolina Scarton, Lucia Specia

We introduce EASSE, a Python package aiming to facilitate and standardise automatic evaluation and comparison of Sentence Simplification (SS) systems.

Reference-less Quality Estimation of Text Simplification Systems

1 code implementation WS 2018 Louis Martin, Samuel Humeau, Pierre-Emmanuel Mazaré, Antoine Bordes, Éric Villemonte de la Clergerie, Benoît Sagot

We show that n-gram-based MT metrics such as BLEU and METEOR correlate the most with human judgment of grammaticality and meaning preservation, whereas simplicity is best evaluated by basic length-based metrics.

Machine Translation Text Simplification +1

ELMoLex: Connecting ELMo and Lexicon Features for Dependency Parsing

no code implementations CONLL 2018 Ganesh Jawahar, Benjamin Muller, Amal Fethi, Louis Martin, {\'E}ric Villemonte de la Clergerie, Beno{\^\i}t Sagot, Djam{\'e} Seddah

We augment the deep Biaffine (BiAF) parser (Dozat and Manning, 2016) with novel features to perform competitively: we utilize an indomain version of ELMo features (Peters et al., 2018) which provide context-dependent word representations; we utilize disambiguated, embedded, morphosyntactic features from lexicons (Sagot, 2018), which complements the existing feature set.

Dependency Parsing Language Modelling

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