Driven by the goal of eradicating language barriers on a global scale, machine translation
has solidified itself as a key focus of artificial intelligence research today. However, such …

We introduce MADLAD-400, a manually audited, general domain 3T token monolingual
dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations …

This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

Italy is characterized by a one-of-a-kind linguistic diversity landscape in Europe, which
implicitly encodes local knowledge, cultural traditions, artistic expressions, and history of its …

The development of neural techniques has opened up new avenues for research in
machine translation. Today, neural machine translation (NMT) systems can leverage highly …

The driving factors behind the development of large language models (LLMs) with
impressive learning capabilities are their colossal model sizes and extensive training …

Large language models (LLMs) implicitly learn to perform a range of language tasks,
including machine translation (MT). Previous studies explore aspects of LLMs' MT …

To advance the neural encoding of Portuguese (PT), and a fortiori the technological
preparation of this language for the digital age, we developed a Transformer-based …

We introduce CroissantLLM, a 1.3 B language model pretrained on a set of 3T English and
French tokens, to bring to the research and industrial community a high-performance, fully …

Turkish is one of the most spoken languages in the world; however, it is still among the low-
resource languages. Wide us of this language on social media platforms such as Twitter …