Thomas Gerald — 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 ↗

2024

Small Language Models Are Good Too: An Empirical Study of Zero-Shot Classification

Pierre Lepagnol, Thomas Gerald, Sahar Ghannay, Christophe Servan, Sophie Rosset

COLING 2024main

This study is part of the debate on the efficiency of large versus small language models for text classification by prompting. We assess the performance of small language models in zero-shot text classification, challenging the prevailing dominance of large models. Across 15 datasets, our investigat…

Cited by 9 Source ↗PDF ↗Scholar ↗