3 citations · 4 across the 6 of their papers we have counts for
6 papers
Long Range Named Entity Recognition for Marathi Documents
Pranita Deshmukh, Nikita Kulkarni, Sanhita Kulkarni +3
The demand for sophisticated natural language processing (NLP) methods, particularly Named Entity Recognition (NER), has increased due to the exponential growth of Marathi-language…
Automated Assessment of Multimodal Answer Sheets in the STEM domain
Rajlaxmi Patil, Aditya Ashutosh Kulkarni, Ruturaj Ghatage +3
In the domain of education, the integration of,technology has led to a transformative era, reshaping traditional,learning paradigms. Central to this evolution is the automation,of…
On Importance of Pruning and Distillation for Efficient Low Resource NLP
Aishwarya Mirashi, Purva Lingayat, Srushti Sonavane +3
The rise of large transformer models has revolutionized Natural Language Processing, leading to significant advances in tasks like text classification. However, this progress deman…
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…
SenTest: Evaluating Robustness of Sentence Encoders
Tanmay Chavan, Shantanu Patankar, Aditya Kane +3
Contrastive learning has proven to be an effective method for pre-training models using weakly labeled data in the vision domain. Sentence transformers are the NLP counterparts to…
Robust Sentiment Analysis for Low Resource languages Using Data Augmentation Approaches: A Case Study in Marathi
Aabha Pingle, Aditya Vyawahare, Isha Joshi +3
Sentiment analysis plays a crucial role in understanding the sentiment expressed in text data. While sentiment analysis research has been extensively conducted in English and other…