Search Results for author: Caroline Brun

Found 23 papers, 4 papers with code

Semantic Context Path Labeling for Semantic Exploration of User Reviews

no code implementations EMNLP (ACL) 2021 Salah Aït-Mokhtar, Caroline Brun, Yves Hoppenot, Agnes Sandor

In this paper we present a prototype demonstrator showcasing a novel method to perform semantic exploration of user reviews.

SMaLL-100: Introducing Shallow Multilingual Machine Translation Model for Low-Resource Languages

3 code implementations20 Oct 2022 Alireza Mohammadshahi, Vassilina Nikoulina, Alexandre Berard, Caroline Brun, James Henderson, Laurent Besacier

In recent years, multilingual machine translation models have achieved promising performance on low-resource language pairs by sharing information between similar languages, thus enabling zero-shot translation.

Machine Translation Translation

What Do Compressed Multilingual Machine Translation Models Forget?

1 code implementation22 May 2022 Alireza Mohammadshahi, Vassilina Nikoulina, Alexandre Berard, Caroline Brun, James Henderson, Laurent Besacier

In this work, we assess the impact of compression methods on Multilingual Neural Machine Translation models (MNMT) for various language groups, gender, and semantic biases by extensive analysis of compressed models on different machine translation benchmarks, i. e. FLORES-101, MT-Gender, and DiBiMT.

Machine Translation Memorization +1

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

2 code implementations6 Dec 2021 Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahendiran, Simon Mille, Ashish Shrivastava, Samson Tan, Tongshuang Wu, Jascha Sohl-Dickstein, Jinho D. Choi, Eduard Hovy, Ondrej Dusek, Sebastian Ruder, Sajant Anand, Nagender Aneja, Rabin Banjade, Lisa Barthe, Hanna Behnke, Ian Berlot-Attwell, Connor Boyle, Caroline Brun, Marco Antonio Sobrevilla Cabezudo, Samuel Cahyawijaya, Emile Chapuis, Wanxiang Che, Mukund Choudhary, Christian Clauss, Pierre Colombo, Filip Cornell, Gautier Dagan, Mayukh Das, Tanay Dixit, Thomas Dopierre, Paul-Alexis Dray, Suchitra Dubey, Tatiana Ekeinhor, Marco Di Giovanni, Tanya Goyal, Rishabh Gupta, Louanes Hamla, Sang Han, Fabrice Harel-Canada, Antoine Honore, Ishan Jindal, Przemyslaw K. Joniak, Denis Kleyko, Venelin Kovatchev, Kalpesh Krishna, Ashutosh Kumar, Stefan Langer, Seungjae Ryan Lee, Corey James Levinson, Hualou Liang, Kaizhao Liang, Zhexiong Liu, Andrey Lukyanenko, Vukosi Marivate, Gerard de Melo, Simon Meoni, Maxime Meyer, Afnan Mir, Nafise Sadat Moosavi, Niklas Muennighoff, Timothy Sum Hon Mun, Kenton Murray, Marcin Namysl, Maria Obedkova, Priti Oli, Nivranshu Pasricha, Jan Pfister, Richard Plant, Vinay Prabhu, Vasile Pais, Libo Qin, Shahab Raji, Pawan Kumar Rajpoot, Vikas Raunak, Roy Rinberg, Nicolas Roberts, Juan Diego Rodriguez, Claude Roux, Vasconcellos P. H. S., Ananya B. Sai, Robin M. Schmidt, Thomas Scialom, Tshephisho Sefara, Saqib N. Shamsi, Xudong Shen, Haoyue Shi, Yiwen Shi, Anna Shvets, Nick Siegel, Damien Sileo, Jamie Simon, Chandan Singh, Roman Sitelew, Priyank Soni, Taylor Sorensen, William Soto, Aman Srivastava, KV Aditya Srivatsa, Tony Sun, Mukund Varma T, A Tabassum, Fiona Anting Tan, Ryan Teehan, Mo Tiwari, Marie Tolkiehn, Athena Wang, Zijian Wang, Gloria Wang, Zijie J. Wang, Fuxuan Wei, Bryan Wilie, Genta Indra Winata, Xinyi Wu, Witold Wydmański, Tianbao Xie, Usama Yaseen, Michael A. Yee, Jing Zhang, Yue Zhang

Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on.

Data Augmentation

Aspect Based Sentiment Analysis into the Wild

no code implementations WS 2018 Caroline Brun, Vassilina Nikoulina

In this paper, we test state-of-the-art Aspect Based Sentiment Analysis (ABSA) systems trained on a widely used dataset on actual data.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)

Transfert de ressources s\'emantiques pour l'analyse de sentiments au niveau des aspects (In this paper, we address the problem of automatic polarity detection in the context of Aspect Based)

no code implementations JEPTALNRECITAL 2018 Caroline Brun

Les informations s{\'e}mantiques riches sont alors extraites de la langue cible par le syst{\`e}me de d{\'e}tection de polarit{\'e}, et ces informations sont ensuite align{\'e}es vers la langue source.

Toward Automatic Understanding of the Function of Affective Language in Support Groups

no code implementations6 Oct 2016 Amit Navindgi, Caroline Brun, Cécile Boulard Masson, Scott Nowson

Understanding expressions of emotions in support forums has considerable value and NLP methods are key to automating this.

Position

Etude de l'image de marque d'entit\'es dans le cadre d'une plateforme de veille sur le Web social

no code implementations JEPTALNRECITAL 2015 Leila Khouas, Caroline Brun, Anne Peradotto, Jean-Val{\`e}re Cossu, Julien Boyadjian, Julien Velcin

Ce travail concerne l{'}int{\'e}gration {\`a} une plateforme de veille sur internet d{'}outils permettant l{'}analyse des opinions {\'e}mises par les internautes {\`a} propos d{'}une entit{\'e}, ainsi que la mani{\`e}re dont elles {\'e}voluent dans le temps.

Un syst\`eme hybride pour l'analyse de sentiments associ\'es aux aspects

no code implementations JEPTALNRECITAL 2015 Caroline Brun, Diana Nicoleta Popa, Claude Roux

Nous pr{\'e}sentons la t{\^a}che et d{\'e}crivons pr{\'e}cis{\'e}ment notre syst{\`e}me qui consiste en une combinaison de composants linguistiques et de modules de classification.

es-en

Investigating the Image of Entities in Social Media: Dataset Design and First Results

no code implementations LREC 2014 Julien Velcin, Young-Min Kim, Caroline Brun, Jean-Yves Dormagen, Eric SanJuan, Leila Khouas, Anne Peradotto, Stephane Bonnevay, Claude Roux, Julien Boyadjian, Alej Molina, ro, Marie Neihouser

The objective of this paper is to describe the design of a dataset that deals with the image (i. e., representation, web reputation) of various entities populating the Internet: politicians, celebrities, companies, brands etc.

Clustering Information Retrieval +2

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