Deep learning has revolutionized the fields of computer vision, natural language
understanding, speech recognition, information retrieval, and more. However, with the …

Recent trends in language modeling have focused on increasing performance through
scaling, and have resulted in an environment where training language models is out of …

Intermediate layer matching is shown as an effective approach for improving knowledge
distillation (KD). However, this technique applies matching in the hidden spaces of two …

While multilingual pretrained language models (LMs) fine-tuned on a single language have
shown substantial cross-lingual task transfer capabilities, there is still a wide performance …

Pre-trained multilingual language models (LMs) have achieved state-of-the-art results in
cross-lingual transfer, but they often lead to an inequitable representation of languages due …

Large pre-trained language models based on transformer architecture have drastically
changed the natural language processing (NLP) landscape. However, deploying those …

Leveraging shared learning through Massively Multilingual Models, state-of-the-art Machine
translation (MT) models are often able to adapt to the paucity of data for low-resource …

Term extraction is an information extraction task at the root of knowledge discovery
platforms. Developing term extractors that are able to generalize across very diverse and …

Scaling dialogue systems to a multitude of domains, tasks and languages relies on costly
and time-consuming data annotation for different domain-task-language configurations. The …

This paper investigates the potential usage of large text-to-image (LTI) models for the
automated diagnosis of a few skin conditions with rarity or a serious lack of annotated …