Acerca de mí

Soy estudiante de doctorado en Ciencias de la Computación en Sorbonne Université y en el equipo de investigación ALMAnaCH en el Inria.

Trabajo principalmente en machine learning, deep learning y procesamiento de lenguaje natural.

Me encanta el café, las galletas y la programación.

Intereses
  • Machine Learning
  • Deep Learning
  • Text Mining
  • NLP
Educación

  • Doctorado en Ciencias de la Computación

    Sorbonne Université

  • Pregrado MIASHS, 2018

    Université Paris 8

  • Master en Matemáticas, 2017

    Aix-Marseille Université

  • Pregrado en Matemáticas, 2016

    Universidad Nacional de Colombia

Publicaciones destacadas

A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
We explore the impact of the training corpus on contextualized word embeddings in five mid-resource languages.
PDF Citar Datos Proyecto Vídeo DOI ACL Anthology ACL 2020 HAL arXiv
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
CamemBERT: a Tasty French Language Model
We explore the impact of the training data size on a French version of RoBERTa.
PDF Citar Datos Proyecto Vídeo DOI ACL Anthology arXiv Website ACL 2020 HAL
CamemBERT: a Tasty French Language Model
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures
We propose a new pipeline to filter, clean and classify Common Crawl by language, we publish the final corpus under the name OSCAR.
PDF Citar Código fuente Datos Proyecto Diapositivas DOI CMLC-7 Website HAL
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures

Publicaciones recientes

SinNer@CLEF-HIPE2020: Sinful Adaptation of SotA models for Named Entity Recognition in Historical French and German Newspapers
In this article we present the approaches developed by the Sorbonne-INRIA for NER (SinNer) team for the CLEF-HIPE 2020 challenge on Named Entity Processing on old newspapers.
PDF Citar Vídeo CEUR-WS CLEF-HIPE-2020 CLEF-2020 HAL
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
We explore the impact of the training corpus on contextualized word embeddings in five mid-resource languages.
PDF Citar Datos Proyecto Vídeo DOI ACL Anthology ACL 2020 HAL arXiv
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
CamemBERT: a Tasty French Language Model
We explore the impact of the training data size on a French version of RoBERTa.
PDF Citar Datos Proyecto Vídeo DOI ACL Anthology arXiv Website ACL 2020 HAL
CamemBERT: a Tasty French Language Model
Building a User-Generated Content North-African Arabizi Treebank: Tackling Hell
We introduce the first treebank for a romanized user-generated content variety of Algerian, a North-African Arabic dialect.
PDF Citar Vídeo DOI ACL Anthology ACL 2020
Les modèles de langue contextuels Camembert pour le Français : impact de la taille et de l'hétérogénéité des données d'entrainement
We explore the impact of the training data size and heterogeneity on French language modeling.
PDF Citar Datos Proyecto TALN 2020 HAL Website
Les modèles de langue contextuels Camembert pour le Français : impact de la taille et de l'hétérogénéité des données d'entrainement
Establishing a New State-of-the-Art for French Named Entity Recognition
We explore convert the NER annotations of the French TreeBank to a more user-friendly format and establish a new state of the art for French NER.
PDF Citar LREC 2020 HAL arXiv ACL Anthology
Establishing a New State-of-the-Art for French Named Entity Recognition
French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
We investigate the impact of different types and size of training corpora on language models.
PDF Citar CMLC-8 ACL Anthology HAL
French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
How OCR Performance can Impact on the Automatic Extraction of Dictionary Content Structures
We explore the impact of the OCR quality on grobid-dictionaries models.
PDF Citar Proyecto TEI 2019 HAL
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures
We propose a new pipeline to filter, clean and classify Common Crawl by language, we publish the final corpus under the name OSCAR.
PDF Citar Código fuente Datos Proyecto Diapositivas DOI CMLC-7 Website HAL
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures

Presentaciones recientes y próximas

Des Méthodes de TAL modernes pour l'Enrichissement de Documents
Nous présentons une pipeline pour le traitement et l’enrichissement de documents basée sur les dernières méthodes d’apprentissage neuronal.
Sep 22, 2020
Diapositivas Follow
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
We explore the impact of the training corpus on contextualized word embeddings in five mid-resource languages.
Jul 6, 2020
Diapositivas Vídeo Follow
A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures
We propose a new pipeline to filter, clean and classify Common Crawl by language, we publish the final corpus under the name OSCAR.
Jul 22, 2019
PDF Código fuente Diapositivas Follow
Preparing the Dictionnaire Universel for Automatic Enrichment
A talk about automatic enrichment of dictionaries.
Jun 13, 2019
Diapositivas Follow
Reducing computation time by months by rewriting Bash scripts in Go
Mar 24, 2019
Código fuente Diapositivas Follow

Proyectos

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All Language Modeling Corpus Linguistics Digital Humanities

BASNUM

Digitization and analysis of Basnage de Beauval’s Universal Dictionary: lexicography and scientific networks

CamemBERT

CamemBERT

A state-of-the-art language model for French.

OSCAR

OSCAR

OSCAR or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus.

Contacto