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pro vyhledávání: '"Bueno, P."'
Autor:
Bueno, Caio
The main question of this paper is the following: how much cancellation can the partial sums restricted to the $k$-free integers up to $x$ of a $\pm 1$ multiplicative function $f$ be in terms of $x$? Building upon the recent paper by Q. Liu, Acta Mat
Externí odkaz:
http://arxiv.org/abs/2411.08268
Autor:
Fama, Israel, Bueno, Bárbara, Alcoforado, Alexandre, Ferraz, Thomas Palmeira, Moya, Arnold, Costa, Anna Helena Reali
In a context where the Brazilian judiciary system, the largest in the world, faces a crisis due to the slow processing of millions of cases, it becomes imperative to develop efficient methods for analyzing legal texts. We introduce uBERT, a hybrid mo
Externí odkaz:
http://arxiv.org/abs/2410.19184
Autor:
Rogerio, R. J. Bueno, de Gracia, G. B.
In this work, we analyze the possibilities of certain gauge transformations regarding some specific spinorial dual structures. To this end, we define a general structure, which can be expressed in terms of discrete symmetry operators associated with
Externí odkaz:
http://arxiv.org/abs/2410.16538
The quantum entanglement phenomenon was demonstrated to operate on a bipartite entangled system composed of two single layers of graphene embedded in an electrolytic medium (which did not permit the transport of electrons) and subjected to an externa
Externí odkaz:
http://arxiv.org/abs/2410.11928
Autor:
Barker, Brandon, Gogilashvili, Mariam, Rodriguez-Bueno, Janiris, Fields, Carl, Dolence, Joshua, Miller, Jonah, Murphy, Jeremiah, Roberts, Luke, Ryan, Benjamin
We introduce the open source code PHOEBUS (phifty one ergs blows up a star) for astrophysical general relativistic radiation magnetohydrodynamic simulations. PHOEBUS is designed for, but not limited to, high energy astrophysical environments such as
Externí odkaz:
http://arxiv.org/abs/2410.09146
Despite the impressive adaptability of large language models (LLMs), challenges remain in ensuring their security, transparency, and interpretability. Given their susceptibility to adversarial attacks, LLMs need to be defended with an evolving combin
Externí odkaz:
http://arxiv.org/abs/2410.07962
Language models are now capable of solving tasks that require dealing with long sequences consisting of hundreds of thousands of tokens. However, they often fail on tasks that require repetitive use of simple rules, even on sequences that are much sh
Externí odkaz:
http://arxiv.org/abs/2410.06396
Autor:
Pérez-Bueno, Fernando, Li, Hongwei Bran, Nasr, Shahin, Caballero-Gaudes, Cesar, Iglesias, Juan Eugenio
While functional Magnetic Resonance Imaging (fMRI) offers valuable insights into cognitive processes, its inherent spatial limitations pose challenges for detailed analysis of the fine-grained functional architecture of the brain. More specifically,
Externí odkaz:
http://arxiv.org/abs/2410.04097
The EU AI Act (EUAIA) introduces requirements for AI systems which intersect with the processes required to establish adversarial robustness. However, given the ambiguous language of regulation and the dynamicity of adversarial attacks, developers of
Externí odkaz:
http://arxiv.org/abs/2410.09078
Large language models are prone to misuse and vulnerable to security threats, raising significant safety and security concerns. The European Union's Artificial Intelligence Act seeks to enforce AI robustness in certain contexts, but faces implementat
Externí odkaz:
http://arxiv.org/abs/2410.05306