Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

Code switching is a prevalent phenomenon in the multilingual community and social media
interaction. In the past ten years, we have witnessed an explosion of code switched data in …

Code-switching is the use of more than one language in the same conversation or utterance.
Recently, multilingual contextual embedding models, trained on multiple monolingual …

Recent trends in NLP research have raised an interest in linguistic code-switching (CS);
modern approaches have been proposed to solve a wide range of NLP tasks on multiple …

Code-switching, the alternation of languages within a conversation or utterance, is a
common communicative phenomenon that occurs in multilingual communities across the …

Pretrained models are a mainstay in modern NLP applications. Pretraining requires access
to large volumes of unlabeled text. While monolingual text is readily available for many of …

Code-mixed languages are very popular in multilingual societies around the world, yet the
resources lag behind to enable robust systems on such languages. A major contributing …

Multilingual question answering (MLQA) is a critical part of an accessible natural language
interface. However, current solutions demonstrate performance far below that of …

Reading comprehension involves the process of reading and understanding textual
information in order to answer questions related to it. It finds practical applications in various …

Since most people in the world today are multilingual, code-switching is ubiquitous in
spoken and written interactions. Paving the way for future adaptive, multilingual …