Anne Vilnat — accepted AI-conference papers

2024

Introducing CQuAE : A New French Contextualised Question-Answering Corpus for the Education Domain

Thomas Gerald, Anne Vilnat, Sofiane Ettayeb, Louis Tamames, Patrick Paroubek

COLING 2024main

We present a new question answering corpus in French designed to educational domain. To be useful in such domain, we have to propose more complex questions and to be able to justify the answers on validated material. We analyze some properties of this corpus. The last part of this paper will be devo…

Cited by 2 Source ↗PDF ↗Scholar ↗

2020

Detecting Non-literal Translations by Fine-tuning Cross-lingual Pre-trained Language Models

Yuming Zhai, Gabriel Illouz, Anne Vilnat

COLING 2020main

Human-generated non-literal translations reflect the richness of human languages and are sometimes indispensable to ensure adequacy and fluency. Non-literal translations are difficult to produce even for human translators, especially for foreign language learners, and machine translations are still…

Cited by 9 Source ↗PDF ↗code ↗Scholar ↗