Large Language Models (LLMs) have demonstrated impressive performance on...
Recent explorations with commercial Large Language Models (LLMs) have sh...
This paper aims to explore the potential of leveraging Large Language Mo...
Visual document understanding is a complex task that involves analyzing ...
Zero-shot cross-lingual transfer is promising, however has been shown to...
With language models becoming increasingly ubiquitous, it has become
ess...
Leveraging shared learning through Massively Multilingual Models,
state-...
Massively Multilingual Language Models (MMLMs) have recently gained
popu...
The Natural Language Inference (NLI) task often requires reasoning over
...
Few-shot transfer often shows substantial gain over zero-shot
transfer <...
Although recent Massively Multilingual Language Models (MMLMs) like mBER...
Borrowing ideas from Production functions in micro-economics, in this
pa...
Massively Multilingual Transformer based Language Models have been obser...
The COVID-19 pandemic has brought out both the best and worst of languag...
The recently proposed CheckList (Riberio et al,. 2020) approach to evalu...
Sentiment analysis is one of the most widely studied applications in NLP...
Natural Language Inference (NLI) is considered a representative task to ...
Recent advancements in NLP have given us models like mBERT and XLMR that...
Development of speech and language technology for social good (LT4SG),
e...
Multilingual language models achieve impressive zero-shot accuracies in ...
Deep Contextual Language Models (LMs) like ELMO, BERT, and their success...
The recent state-of-the-art natural language understanding (NLU) systems...
Neural models excel at extracting statistical patterns from large amount...
Ethical aspects of research in language technologies have received much
...
Pre-trained Transformer-based neural architectures have consistently ach...
Code-switching is the use of more than one language in the same conversa...
Language technologies contribute to promoting multilingualism and lingui...
Natural Language Inference (NLI) is the task of inferring the logical
re...
In this paper, we examine and analyze the challenges associated with
dev...
In this paper, we present a set of computational methods to identify the...
Code-mixing or code-switching are the effortless phenomena of natural
sw...
We make one of the first attempts to build working models for
intra-sent...