This paper explores the potential of leveraging Large Language Models (LLMs) for data
augmentation in multilingual commonsense reasoning datasets where the available training …

Understanding the sentiment of a comment from a video or an image is an essential task in
many applications. Sentiment analysis of a text can be useful for various decision-making …

This paper describes the development of a multilingual, manually annotated dataset for
three under-resourced Dravidian languages generated from social media comments. The …

Abstract We introduce Kannada CodeMixed Dataset (KanCMD), a multi-task learning
dataset for sentiment analysis and offensive language identification. The KanCMD dataset …

Code-Switching, a common phenomenon in written text and conversation, has been studied
over decades by the natural language processing (NLP) research community. Initially, code …

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 …

This paper demonstrates our work for the shared task on Offensive Language Identification
in Dravidian Languages-EACL 2021. Offensive language detection in the various social …

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

The analysis of data in which multiple languages are represented has gained popularity
among computational linguists in recent years. So far, much of this research focuses mainly …

In this paper, we utilize the pre-trained embedding, sub-word embedding and closely related
languages of languages in the code mixed corpus to create a meta-embedding. We then …