This article presents a comprehensive and practical guide for practitioners and end-users
working with Large Language Models (LLMs) in their downstream Natural Language …

We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

Recent advances in the pre-training of language models leverage large-scale datasets to
create multilingual models. However, low-resource languages are mostly left out in these …

Cross-lingual named entity recognition (CrossNER) faces challenges stemming from
uneven performance due to the scarcity of multilingual corpora, especially for non-English …

Pre-trained models have achieved remarkable success in natural language processing
(NLP). However, existing pre-training methods underutilize the benefits of language …

Multilingual Machine Translation promises to improve translation quality between non-
English languages. This is advantageous for several reasons, namely lower latency (no …

We present the results of the WMT'22 SharedTask on Large-Scale Machine Translation
Evaluation for African Languages. The shared taskincluded both a data and a systems track …

We present the results of the first task on Large-Scale Multilingual Machine Translation. The
task consists on the many-to-many evaluation of a single model across a variety of source …

This paper describes Tencent's multilingual machine translation systems for the WMT22
shared task on Large-Scale Machine Translation Evaluation for African Languages. We …

Recently, there has been increasing interest in exploring the capabilities of advanced large
language models (LLMs) in the field of information extraction (IE), specifically focusing on …