116 citations · 272 across the 10 of their papers we have counts for
11 papers
On the cross-lingual transferability of multilingual prototypical models across NLU tasks
Oralie Cattan, Christophe Servan, Sophie Rosset
Supervised deep learning-based approaches have been applied to task-oriented dialog and have proven to be effective for limited domain and language applications when a sufficient n…
Benchmarking Transformers-based models on French Spoken Language Understanding tasks
Oralie Cattan, Sahar Ghannay, Christophe Servan +1
In the last five years, the rise of the self-attentional Transformer-based architectures led to state-of-the-art performances over many natural language tasks. Although these appro…
On the Usability of Transformers-based models for a French Question-Answering task
Oralie Cattan, Christophe Servan, Sophie Rosset
For many tasks, state-of-the-art results have been achieved with Transformer-based architectures, resulting in a paradigmatic shift in practices from the use of task-specific archi…
Using Whole Document Context in Neural Machine Translation
Valentin Macé, Christophe Servan
In Machine Translation, considering the document as a whole can help to resolve ambiguities and inconsistencies. In this paper, we propose a simple yet promising approach to add co…
Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases
Estelle Maudet, Oralie Cattan, Maureen de Seyssel +1
This paper reports on Qwant Research contribution to tasks 2 and 3 of the DEFT 2019's challenge, focusing on French clinical cases analysis. Task 2 is a task on semantic similarity…
Image search using multilingual texts: a cross-modal learning approach between image and text
Maxime Portaz, Hicham Randrianarivo, Adrien Nivaggioli +3
Multilingual (or cross-lingual) embeddings represent several languages in a unique vector space. Using a common embedding space enables for a shared semantic between words from dif…