Zobrazeno 1 - 10
of 103 482
pro vyhledávání: '"de Melo AS"'
Autor:
Hipólito-Ricaldi, Wiliam S., von Marttens, Rodrigo, de Melo-Santos, Felipe, Rodrigues, Davi C.
We investigate the observational implications of a gravitational model wherein the gravitational constant $G$ and the cosmological constant $\Lambda$ exhibit scale-dependent behavior at the perturbative level, while preserving the General Relativity
Externí odkaz:
http://arxiv.org/abs/2411.12097
In this paper, the emission of gravitational waves in quadratic gravity theory is examined. The wave equations for massless and massive perturbations are derived, followed by the calculation of the energy and angular momentum radiated. In the quadrup
Externí odkaz:
http://arxiv.org/abs/2411.10098
Autor:
de Melo, Fernando, Carvalho, Gabriel Dias, Correia, Pedro S., Obando, Paola Concha, de Oliveira, Thiago R., Vallejos, Raúl O.
Quantum mechanics started out as a theory to describe the smallest scales of energy in Nature. After hundred years of development it is now routinely employed to describe, for example, quantum computers with thousands of qubits. This tremendous progr
Externí odkaz:
http://arxiv.org/abs/2411.07327
Autor:
de Melo, Raphaela Fernandes, Lombardo, Linda, Puls, Arthur Alencastro, Romano, Donatella, Hansen, Camilla Juul, Tsiatsiou, Sophie, Meynet, Georges
Context. Carbon, nitrogen, and oxygen are the most abundant elements throughout the universe, after hydrogen and helium. Studying these elements in low-metallicity stars can provide crucial information on the chemical composition in the early Galaxy
Externí odkaz:
http://arxiv.org/abs/2411.04180
Autor:
Abada, Asmaa, Bernal, Nicolás, Hernández, Antonio E. Cárcamo, Kovalenko, Sergey, de Melo, Téssio B., Toma, Takashi
In this talk, we discuss the phenomenology of radiative 3-loop seesaw models. The 3-loop suppression allows the new particles to have masses at the TeV scale, along with relatively large Yukawa couplings, while retaining consistency with neutrino mas
Externí odkaz:
http://arxiv.org/abs/2411.00020
Heterogeneous graph neural networks have recently gained attention for long document summarization, modeling the extraction as a node classification task. Although effective, these models often require external tools or additional machine learning mo
Externí odkaz:
http://arxiv.org/abs/2410.21315
Autor:
Kohlenberg, Leo, Horns, Leonard, Sadrieh, Frederic, Kiele, Nils, Clausen, Matthis, Ketterer, Konstantin, Navasardyan, Avetis, Czinczoll, Tamara, de Melo, Gerard, Herbrich, Ralf
Annotating large datasets can be challenging. However, crowd-sourcing is often expensive and can lack quality, especially for non-trivial tasks. We propose a method of using LLMs as few-shot learners for annotating data in a complex natural language
Externí odkaz:
http://arxiv.org/abs/2410.12470
Autor:
Rivera, Corban, Byrd, Grayson, Paul, William, Feldman, Tyler, Booker, Meghan, Holmes, Emma, Handelman, David, Kemp, Bethany, Badger, Andrew, Schmidt, Aurora, Jatavallabhula, Krishna Murthy, de Melo, Celso M, Seenivasan, Lalithkumar, Unberath, Mathias, Chellappa, Rama
Robotic planning and execution in open-world environments is a complex problem due to the vast state spaces and high variability of task embodiment. Recent advances in perception algorithms, combined with Large Language Models (LLMs) for planning, of
Externí odkaz:
http://arxiv.org/abs/2410.06108
Scalable Vector Graphics (SVG) is a popular format on the web and in the design industry. However, despite the great strides made in generative modeling, SVG has remained underexplored due to the discrete and complex nature of such data. We introduce
Externí odkaz:
http://arxiv.org/abs/2410.05991
Autor:
Thimonier, Hugo, Costa, José Lucas De Melo, Popineau, Fabrice, Rimmel, Arpad, Doan, Bich-Liên
Self-supervision is often used for pre-training to foster performance on a downstream task by constructing meaningful representations of samples. Self-supervised learning (SSL) generally involves generating different views of the same sample and thus
Externí odkaz:
http://arxiv.org/abs/2410.05016