Transformer-based pretrained language models (T-PTLMs) have achieved great success in
almost every NLP task. The evolution of these models started with GPT and BERT. These …

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 …

Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …

Research on prompting has shown excellent performance with little or even no supervised
training across many tasks. However, prompting for machine translation is still under …

One of the biggest challenges hindering progress in low-resource and multilingual machine
translation is the lack of good evaluation benchmarks. Current evaluation benchmarks either …

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

Large language models have led to remarkable progress on many NLP tasks, and
researchers are turning to ever-larger text corpora to train them. Some of the largest corpora …

In this multicultural age, language translation is one of the most performed tasks, and it is
becoming increasingly AI-moderated and automated. As a novel AI system, ChatGPT claims …

In this work, we present an information-theoretic framework that formulates cross-lingual
language model pre-training as maximizing mutual information between multilingual-multi …

Question answering (QA) models have shown rapid progress enabled by the availability of
large, high-quality benchmark datasets. Such annotated datasets are difficult and costly to …