Learning paradigms for large language models (LLMs) currently tend to fa...
Automatic evaluation of machine translation (MT) is a critical tool driv...
Trustworthy answer content is abundant in many high-resource languages a...
Data scarcity is a crucial issue for the development of highly multiling...
Contrastive learning has been successfully used for retrieval of semanti...
Recent neural network-based language models have benefited greatly from
...
We introduce XTREME-S, a new benchmark to evaluate universal cross-lingu...
Unsupervised pre-training is now the predominant approach for both text ...
Pipelined NLP systems have largely been superseded by end-to-end neural
...
The traditional image captioning task uses generic reference captions to...
Linguists characterize dialects by the presence, absence, and frequency ...
Multilingual question answering tasks typically assume answers exist in ...
Confidently making progress on multilingual modeling requires challengin...