Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Asani, Saina"'
Autor:
Ataiefard, Foozhan, Ahmed, Walid, Hajimolahoseini, Habib, Asani, Saina, Javadi, Farnoosh, Hassanpour, Mohammad, Awad, Omar Mohamed, Wen, Austin, Liu, Kangling, Liu, Yang
Vision transformers are known to be more computationally and data-intensive than CNN models. These transformer models such as ViT, require all the input image tokens to learn the relationship among them. However, many of these tokens are not informat
Externí odkaz:
http://arxiv.org/abs/2401.15293
Autor:
Javadi, Farnoosh, Ahmed, Walid, Hajimolahoseini, Habib, Ataiefard, Foozhan, Hassanpour, Mohammad, Asani, Saina, Wen, Austin, Awad, Omar Mohamed, Liu, Kangling, Liu, Yang
Massive transformer-based models face several challenges, including slow and computationally intensive pre-training and over-parametrization. This paper addresses these challenges by proposing a versatile method called GQKVA, which generalizes query,
Externí odkaz:
http://arxiv.org/abs/2311.03426