- LiLowLa (2022-2025): Lightweight neural translation technologies for low-resource languages. The main objectives of the project are: The development of a smart crawling method able to prioritize the most productive websites; the development of data augmentation techniques for training neural machine translation systems for low-resource languages; to devise a method for distilling the translation knowledge encoded in large pre-trained models; to enable translation memory-based computer-aided translation tools to exploit target-language monolingual corpora; and to deepen the understanding of how NMT systems behave at prediction time and during training. Project website.