Zobrazeno 1 - 10
of 107 714
pro vyhledávání: '"de Melo AS"'
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
In a recent paper we studied the cosmology of Nonminimal Derivative Coupling (NDC) between gravity and a scalar field, which is a non-trivial class of Horndeski. We have shown that it presents a variety of solutions for the scale factor, but there ar
Externí odkaz:
http://arxiv.org/abs/2410.04624
Autor:
Ouyang, Zetian, Qiu, Yishuai, Wang, Linlin, de Melo, Gerard, Zhang, Ya, Wang, Yanfeng, He, Liang
With the proliferation of Large Language Models (LLMs) in diverse domains, there is a particular need for unified evaluation standards in clinical medical scenarios, where models need to be examined very thoroughly. We present CliMedBench, a comprehe
Externí odkaz:
http://arxiv.org/abs/2410.03502
Autor:
Barros, Pablo M., Sardinha, Roosevelt de L., Arboleda, Giovanny A. M., Valente, Lessandro de S. S., de Melo, Isabelle R. V., Aveleda, Albino, Bulcão, André, Netto, Sergio L., Evsukoff, Alexandre G.
The recent development of deep learning (DL) methods for computer vision has been driven by the creation of open benchmark datasets on which new algorithms can be tested and compared with reproducible results. Although DL methods have many applicatio
Externí odkaz:
http://arxiv.org/abs/2410.08231
Publikováno v:
Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II. Vol. 13035. SPIE, 2024
In this work, we explore the possibility of using synthetically generated data for video-based gesture recognition with large pre-trained models. We consider whether these models have sufficiently robust and expressive representation spaces to enable
Externí odkaz:
http://arxiv.org/abs/2410.02152
Autor:
Aguilar, A. C., Bashir, A., Cobos-Martínez, J. J., Courtoy, A., El-Bennich, B., de Florian, D., Frederico, T., Gonçalves, V. P., Hentschinski, M., Hernández-Pinto, R. J., Krein, G., Machado, M. V. T., de Melo, J. P. B. C., de Paula, W., Sassot, R., Serna, F. E., Albino, L., Borsa, I., Cieri, L., Mazzitelli, J., Miramontes, Á., Raya, K., Salazar, F., Sborlini, G., Zurita, P.
The Electron-Ion Collider, a next generation electron-hadron and electron-nuclei scattering facility, will be built at Brookhaven National Laboratory. The wealth of new data will shape research in hadron physics, from nonperturbative QCD techniques t
Externí odkaz:
http://arxiv.org/abs/2409.18407
Autor:
Glicenstein, Antoine, Apoorva, Apoorva, Orenes, Daniel Benedicto, Letellier, Hector, de Melo, Alvaro Mitchell Galvão, Saint-Jalm, Raphaël, Kaiser, Robin
This study introduces a novel method to investigate in-situ light transport within optically thick ensembles of cold atoms, exploiting the internal structure of alkaline-earth metals. A method for creating an optical excitation at the center of a lar
Externí odkaz:
http://arxiv.org/abs/2409.11117