Zobrazeno 1 - 10
of 60 756
pro vyhledávání: '"A. Munir"'
Publikováno v:
Breast, Vol 68, Iss , Pp S118-S119 (2023)
Externí odkaz:
https://doaj.org/article/311e811c181a467e97e7cdcba6558aa7
Extending the Standard Model (SM) by one additional Higgs doublet leads to the Two-Higgs Doublet Model (2HDM). A specific charge assignment of the SM fermions under the $\mathbb{Z}_2$ symmetry leads to the Type-I 2HDM. A key feature of the Type-I 2HD
Externí odkaz:
http://arxiv.org/abs/2409.19643
Autor:
Jiang, Yifan, Aggarwal, Kriti, Laud, Tanmay, Munir, Kashif, Pujara, Jay, Mukherjee, Subhabrata
The rapid progress of Large Language Models (LLMs) has opened up new opportunities across various domains and applications; yet it also presents challenges related to potential misuse. To mitigate such risks, red teaming has been employed as a proact
Externí odkaz:
http://arxiv.org/abs/2409.17458
Autor:
Shah, Shahid Munir, Gillani, Syeda Anshrah, Baig, Mirza Samad Ahmed, Saleem, Muhammad Aamer, Siddiqui, Muhammad Hamzah
This study investigates the use of Large Language Models (LLMs) for improved depression detection from users social media data. Through the use of fine-tuned GPT 3.5 Turbo 1106 and LLaMA2-7B models and a sizable dataset from earlier studies, we were
Externí odkaz:
http://arxiv.org/abs/2409.14794
Accurate weather and climate modeling is critical for both scientific advancement and safeguarding communities against environmental risks. Traditional approaches rely heavily on Numerical Weather Prediction (NWP) models, which simulate energy and ma
Externí odkaz:
http://arxiv.org/abs/2409.07585
Autor:
Khan, Asifullah, Sohail, Anabia, Fiaz, Mustansar, Hassan, Mehdi, Afridi, Tariq Habib, Marwat, Sibghat Ullah, Munir, Farzeen, Ali, Safdar, Naseem, Hannan, Zaheer, Muhammad Zaigham, Ali, Kamran, Sultana, Tangina, Tanoli, Ziaurrehman, Akhter, Naeem
Deep supervised learning models require high volume of labeled data to attain sufficiently good results. Although, the practice of gathering and annotating such big data is costly and laborious. Recently, the application of self supervised learning (
Externí odkaz:
http://arxiv.org/abs/2408.17059
Autor:
Munir, Farzeen, Kucner, Tomasz Piotr
The advancement of socially-aware autonomous vehicles hinges on precise modeling of human behavior. Within this broad paradigm, the specific challenge lies in accurately predicting pedestrian's trajectory and intention. Traditional methodologies have
Externí odkaz:
http://arxiv.org/abs/2407.17162
Compositional Zero-Shot Learning (CZSL) aims to predict unknown compositions made up of attribute and object pairs. Predicting compositions unseen during training is a challenging task. We are exploring Open World Compositional Zero-Shot Learning (OW
Externí odkaz:
http://arxiv.org/abs/2407.13715
Publikováno v:
Proceedings of Blockchain-2024
In this paper, we present a study of a Federated Learning (FL) system, based on the use of decentralized architectures to ensure trust and increase reliability. The system is based on the idea that the FL collaborators upload the (ciphered) model par
Externí odkaz:
http://arxiv.org/abs/2407.06862
Multi-robot coverage is crucial in numerous applications, including environmental monitoring, search and rescue operations, and precision agriculture. In modern applications, a multi-robot team must collaboratively explore unknown spatial fields in G
Externí odkaz:
http://arxiv.org/abs/2407.06296