Much recent progress in applications of machine learning models to NLP has been driven
by benchmarks that evaluate models across a wide variety of tasks. However, these broad …

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 …

Progress in cross-lingual modeling depends on challenging, realistic, and diverse
evaluation sets. We introduce Multilingual Knowledge Questions and Answers (MKQA), an …

Practical active noise control (ANC) systems, like the active noise cancellation headphone,
usually adopt a control filter with preset coefficients to achieve satisfactory noise reduction …

Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with
pretrained encoders like multilingual BERT. Despite its growing popularity, little to no …

We review motivations, definition, approaches, and methodology for unsupervised cross-
lingual learning and call for a more rigorous position in each of them. An existing rationale …

In this paper, we address the task of zero-shot cross-lingual news sentiment classification.
Given the annotated dataset of positive, neutral, and negative news in Slovene, the aim is to …

Recent advances in the field of natural language processing has improved state-of-the-art
performances on many tasks including question answering for languages like English …

While recent work on multilingual language models has demonstrated their capacity for
cross-lingual zero-shot transfer on downstream tasks, there is a lack of consensus in the …

Multilingual pre-trained models are able to zero-shot transfer knowledge from rich-resource
to low-resource languages in machine reading comprehension (MRC). However, inherent …