Multilingual large language models (MLLMs) are jointly trained on data f...
Data scarcity is a crucial issue for the development of highly multiling...
Current image generation models struggle to reliably produce well-formed...
Evaluation metrics that are not robust to dialect variation make it
impo...
Large multilingual language models typically share their parameters acro...
We present FRMT, a new dataset and evaluation benchmark for Few-shot
Reg...
Recent neural network-based language models have benefited greatly from
...
Pre-trained language models perform well on a variety of linguistic task...
Pipelined NLP systems have largely been superseded by end-to-end neural
...
State-of-the-art multilingual models depend on vocabularies that cover a...
Confidently making progress on multilingual modeling requires challengin...
In this paper, we show that Multilingual BERT (M-BERT), released by Devl...
Compositor attribution, the clustering of pages in a historical printed
...
We describe DyNet, a toolkit for implementing neural network models base...