Amir Hazem author Mérieme Bouhandi author Florian Boudin author Beatrice Daille author 2020-may text English eng European Language Resources Association Marseille, France conference publication 979-10-95546-57-3 Automatic terminology extraction is a notoriously difficult task aiming to ease effort demanded to manually identify terms in domain-specific corpora by automatically providing a ranked list of candidate terms. The main ways that addressed this task can be ranged in four main categories: (i) rule-based approaches, (ii) feature-based approaches, (iii) context-based approaches, and (iv) hybrid approaches. For this first TermEval shared task, we explore a feature-based approach, and a deep neural network multitask approach -BERT- that we fine-tune for term extraction. We show that BERT models (RoBERTa for English and CamemBERT for French) outperform other systems for French and English languages. hazem-etal-2020-termeval https://www.aclweb.org/anthology/2020.computerm-1.13 2020-may 95 100