21 citations · 50 across the 15 of their papers we have counts for
15 papers
Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A Case Study in Marathi
Pranita Deshmukh, Nikita Kulkarni, Sanhita Kulkarni +2
With the surge in digital content in low-resource languages, there is an escalating demand for advanced Natural Language Processing (NLP) techniques tailored to these languages. BE…
Curating Stopwords in Marathi: A TF-IDF Approach for Improved Text Analysis and Information Retrieval
Rohan Chavan, Gaurav Patil, Vishal Madle +1
Stopwords are commonly used words in a language that are often considered to be of little value in determining the meaning or significance of a document. These words occur frequent…
TextGram: Towards a better domain-adaptive pretraining
Sharayu Hiwarkhedkar, Saloni Mittal, Vidula Magdum +4
For green AI, it is crucial to measure and reduce the carbon footprint emitted during the training of large language models. In NLP, performing pre-training on Transformer models r…
L3Cube-MahaNews: News-based Short Text and Long Document Classification Datasets in Marathi
Saloni Mittal, Vidula Magdum, Omkar Dhekane +2
The availability of text or topic classification datasets in the low-resource Marathi language is limited, typically consisting of fewer than 4 target labels, with some achieving n…
MahaSQuAD: Bridging Linguistic Divides in Marathi Question-Answering
Ruturaj Ghatage, Aditya Kulkarni, Rajlaxmi Patil +2
Question-answering systems have revolutionized information retrieval, but linguistic and cultural boundaries limit their widespread accessibility. This research endeavors to bridge…
L3Cube-IndicNews: News-based Short Text and Long Document Classification Datasets in Indic Languages
Aishwarya Mirashi, Srushti Sonavane, Purva Lingayat +2
In this work, we introduce L3Cube-IndicNews, a multilingual text classification corpus aimed at curating a high-quality dataset for Indian regional languages, with a specific focus…