Zobrazeno 1 - 10
of 2 521
pro vyhledávání: '"P Geetanjali"'
Autor:
Bihani, Geetanjali, Rayz, Julia
The advent of pre-trained language models (PLMs) has enabled significant performance gains in the field of natural language processing. However, recent studies have found PLMs to suffer from miscalibration, indicating a lack of accuracy in the confid
Externí odkaz:
http://arxiv.org/abs/2412.15269
Autor:
Sharma, Geetanjali, Tandon, Abhishek, Jaswal, Gaurav, Nigam, Aditya, Ramachandra, Raghavendra
Iris recognition technology plays a critical role in biometric identification systems, but their performance can be affected by variations in iris pigmentation. In this work, we investigate the impact of iris pigmentation on the efficacy of biometric
Externí odkaz:
http://arxiv.org/abs/2411.08490
Autor:
Deshmukh, Pranita, Kulkarni, Nikita, Kulkarni, Sanhita, Manghani, Kareena, Kale, Geetanjali, Joshi, Raviraj
The demand for sophisticated natural language processing (NLP) methods, particularly Named Entity Recognition (NER), has increased due to the exponential growth of Marathi-language digital content. In particular, NER is essential for recognizing dist
Externí odkaz:
http://arxiv.org/abs/2410.09192
This work proposes a secure and dynamic VM allocation strategy for multi-tenant distributed systems using the Thompson sampling approach. The method proves more effective and secure compared to epsilon-greedy and upper confidence bound methods, showi
Externí odkaz:
http://arxiv.org/abs/2410.04363
Autor:
Patil, Rajlaxmi, Kulkarni, Aditya Ashutosh, Ghatage, Ruturaj, Endait, Sharvi, Kale, Geetanjali, Joshi, Raviraj
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 grading processes, particularly within the STEM domain encompassing Sc
Externí odkaz:
http://arxiv.org/abs/2409.15749
Autor:
Mirashi, Aishwarya, Lingayat, Purva, Sonavane, Srushti, Padhiyar, Tejas, Joshi, Raviraj, Kale, Geetanjali
The rise of large transformer models has revolutionized Natural Language Processing, leading to significant advances in tasks like text classification. However, this progress demands substantial computational resources, escalating training duration,
Externí odkaz:
http://arxiv.org/abs/2409.14162
Autor:
Tandon, Abhishek, Sharma, Geetanjali, Jaswal, Gaurav, Nigam, Aditya, Ramachandra, Raghavendra
Recent studies have emphasized the potential of forehead-crease patterns as an alternative for face, iris, and periocular recognition, presenting contactless and convenient solutions, particularly in situations where faces are covered by surgical mas
Externí odkaz:
http://arxiv.org/abs/2408.15693
With the impressive performance in various downstream tasks, large language models (LLMs) have been widely integrated into production pipelines, like recruitment and recommendation systems. A known issue of models trained on natural language data is
Externí odkaz:
http://arxiv.org/abs/2405.06687
Autor:
Hiwarkhedkar, Sharayu, Mittal, Saloni, Magdum, Vidula, Dhekane, Omkar, Joshi, Raviraj, Kale, Geetanjali, Ladkat, Arnav
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 requires significant computational resources. This pre-training involve
Externí odkaz:
http://arxiv.org/abs/2404.18228
Biometric authentication, which utilizes contactless features, such as forehead patterns, has become increasingly important for identity verification and access management. The proposed method is based on learning a 3D spatio-spatial temporal convolu
Externí odkaz:
http://arxiv.org/abs/2403.16202