Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …

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

What does it take to create the Babel Fish, a tool that can help individuals translate speech
between any two languages? While recent breakthroughs in text-based models have …

Scaling multilingual representation learning beyond the hundred most frequent languages is
challenging, in particular to cover the long tail of low-resource languages. A promising …

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

We present FRMT, a new dataset and evaluation benchmark for Few-shot Region-aware
Machine Translation, a type of style-targeted translation. The dataset consists of professional …

Neural machine translation (NMT) has progressed rapidly over the past several years, and
modern models are able to achieve relatively high quality using only monolingual text data …

Modern machine translation models and language models are able to translate without
having been trained on parallel data, greatly expanding the set of languages that they can …

Although existing multilingual neural machine translation (MNMT) models have
demonstrated remarkable performance to handle multiple translation directions in a single …

Foundational models with billions of parameters which have been trained on large corpora
of data have demonstrated non-trivial skills in a variety of domains. However, due to their …