Zobrazeno 1 - 10
of 26 406
pro vyhledávání: '"Lloret, A."'
Autor:
Cobo, Miriam, del Barrio, Amaia Pérez, Fernández-Miranda, Pablo Menéndez, Bellón, Pablo Sanz, Iglesias, Lara Lloret, Silva, Wilson
Prognosis after intracranial hemorrhage (ICH) is influenced by a complex interplay between imaging and tabular data. Rapid and reliable prognosis are crucial for effective patient stratification and informed treatment decision-making. In this study,
Externí odkaz:
http://arxiv.org/abs/2408.08784
We present ALT (ALignment with Textual feedback), an approach that aligns language models with user preferences expressed in text. We argue that text offers greater expressiveness, enabling users to provide richer feedback than simple comparative pre
Externí odkaz:
http://arxiv.org/abs/2407.16970
Autor:
Maestre, María Miró, Martínez-Murillo, Iván, Martin, Tania J., Navarro-Colorado, Borja, Ferrández, Antonio, Cueto, Armando Suárez, Lloret, Elena
Generative Artificial Intelligence has grown exponentially as a result of Large Language Models (LLMs). This has been possible because of the impressive performance of deep learning methods created within the field of Natural Language Processing (NLP
Externí odkaz:
http://arxiv.org/abs/2407.10554
We have previously presented the idea of how complex multimodal information could be represented in our brains in a compressed form, following mechanisms similar to those employed in machine learning tools, like autoencoders. In this short comment no
Externí odkaz:
http://arxiv.org/abs/2406.09940
Autor:
Ferrández, Antonio, Lavigne-Cerván, Rocío, Peral, Jesús, Navarro-Soria, Ignasi, Lloret, Ángel, Gil, David, Rocamora, Carmen
Publikováno v:
PeerJ Computer Science, Volume 10, February 2024, ID e1866
In this article, we present CuentosIE (TalesEI: chatbot of tales with a message to develop Emotional Intelligence), an educational chatbot on emotions that also provides teachers and psychologists with a tool to monitor their students/patients throug
Externí odkaz:
http://arxiv.org/abs/2403.07193
Autor:
Benamra, Yamina, Auvray, Laurent, Andrieux, Jérôme, Cauwet, François, Alegre, Maria-Paz, Lloret, Fernando, Araujo, Daniel, Gutierrez, Marina, Ferro, Gabriel
In this work, the successful heteroepitaxial growth of boron carbide (B x C) on 4HSiC(0001) 4{\textdegree} off substrate using chemical vapor deposition (CVD) is reported. Towards this end, a two-step procedure was developed, involving the 4H-SiC sub
Externí odkaz:
http://arxiv.org/abs/2310.17221
In high-stakes settings, Machine Learning models that can provide predictions that are interpretable for humans are crucial. This is even more true with the advent of complex deep learning based models with a huge number of tunable parameters. Recent
Externí odkaz:
http://arxiv.org/abs/2309.11155
Publikováno v:
Nonlinear Processes in Geophysics, Vol 31, Pp 515-533 (2024)
The design and implementation of boundary conditions for the robust generation and simulation of periodic finite-amplitude internal waves is examined in a quasi two-layer continuous stratification using a spectral-element-method-based incompressible
Externí odkaz:
https://doaj.org/article/fff4d6ca75f84f46b2b10eff11bcb3b2
Autor:
Nadin Memar, Ryan Sherrard, Aditya Sethi, Carla Lloret Fernandez, Henning Schmidt, Eric J. Lambie, Richard J. Poole, Ralf Schnabel, Barbara Conradt
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Abstract We report that the eukaryotic replicative helicase CMG (Cdc45-MCM-GINS) is required for differential gene expression in cells produced by asymmetric cell divisions in C. elegans. We found that the C. elegans CMG component, PSF-2 GINS2, is ne
Externí odkaz:
https://doaj.org/article/6eec216ab0a34138b88af544db4362f7
Autor:
Leal Filho, Walter, Dinis, Maria Alzira Pimenta, Morales, Maria F., Semitiel-García, María, Noguera-Méndez, Pedro, Ruiz de Maya, Salvador, Alarcón-del-Amo, María-del-Carmen, Esteban-Lloret, Nuria, Pemartín, María
Publikováno v:
International Journal of Sustainability in Higher Education, 2024, Vol. 25, Issue 6, pp. 1156-1179.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJSHE-08-2023-0382