Pedro Javier Ortiz Suárez

Doctorante

Sorbonne Université

Inria

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

Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets

We audit 5 multilingual corpora, finding that lower-resource corpora have systematic issues.

Isaac Caswell, Julia Kreutzer, Lisa Wang, Ahsan Wahab, Daan van Esch, Nasanbayar Ulzii-Orshikh, Allahsera Tapo, Nishant Subramani, Artem Sokolov, Claytone Sikasote, Monang Setyawan, Supheakmungkol Sarin, Sokhar Samb, Benoît Sagot, Clara Rivera, Annette Rios, Isabel Papadimitriou, Salomey Osei, Pedro Javier Ortiz Suárez, Iroro Orife, Kelechi Ogueji, Rubungo Andre Niyongabo, Toan Q. Nguyen, Mathias Müller, André Müller, Shamsuddeen Hassan Muhammad, Nanda Muhammad, Ayanda Mnyakeni, Jamshidbek Mirzakhalov, Tapiwanashe Matangira, Colin Leong, Nze Lawson, Sneha Kudugunta, Yacine Jernite, Mathias Jenny, Orhan Firat, Bonaventure F. P. Dossou, Sakhile Dlamini, Nisansa de Silva, Sakine Çabuk Ballı, Stella Biderman, Alessia Battisti, Ahmed Baruwa, Ankur Bapna, Pallavi Baljekar, Israel Abebe Azime, Ayodele Awokoya, Duygu Ataman, Orevaoghene Ahia, Oghenefego Ahia, Sweta Agrawal, Mofetoluwa Adeyemi

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.

Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot

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.

Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé Seddah, Benoît Sagot

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.

Pedro Javier Ortiz Suárez, Benoît Sagot, Laurent Romary

Asynchronous Pipeline for Processing Huge Corpora on Medium to Low Resource Infrastructures

Publicaciones recientes

Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets

We audit 5 multilingual corpora, finding that lower-resource corpora have systematic issues.

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.

Pedro Javier Ortiz Suárez, Yoann Dupont, Gaël Lejeune, Tian Tian

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.

Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot

CamemBERT: a Tasty French Language Model

We explore the impact of the training data size on a French version of RoBERTa.

Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Djamé Seddah, Benoît Sagot

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.

Djamé Seddah, Farah Essaidi, Amal Fethi, Matthieu Futeral, Benjamin Muller, Pedro Javier Ortiz Suárez, Benoît Sagot, Abhishek Srivastava

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.

Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, Yoann Dupont, Laurent Romary, Éric de la Clergerie, Benoît Sagot, Djamé Seddah

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.

Pedro Javier Ortiz Suárez, Yoann Dupont, Benjamin Muller, Laurent Romary, Benoît Sagot

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.

Murielle Popa-Fabre, Pedro Javier Ortiz Suárez, Benoît Sagot, Éric de la Clergerie

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.

Mohamed Khemakhem, Ioana Galleron, Geoffrey Williams, Laurent Romary, Pedro Javier Ortiz Suárez

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.

Pedro Javier Ortiz Suárez, Benoît Sagot, Laurent Romary

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.

Pedro Javier Ortiz Suárez

Sep 22, 2020

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.

Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot

Jul 6, 2020

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.

Pedro Javier Ortiz Suárez, Benoît Sagot, Laurent Romary

Jul 22, 2019

Preparing the Dictionnaire Universel for Automatic Enrichment

A talk about automatic enrichment of dictionaries.

Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot

Jun 13, 2019

Reducing computation time by months by rewriting Bash scripts in Go

Pedro Javier Ortiz Suárez

Mar 24, 2019

Proyectos

BASNUM

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

CamemBERT

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

OSCAR

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

Pedro Javier Ortiz Suárez

Doctorante

Sorbonne Université

Inria

Acerca de mí

Publicaciones destacadas

Publicaciones recientes

Presentaciones recientes y próximas

Proyectos

BASNUM

CamemBERT

OSCAR

Contacto