Zobrazeno 1 - 10
of 813
pro vyhledávání: '"Ortiz, Juan P. A."'
While large language models (LLMs) are increasingly playing a pivotal role in education by providing instantaneous, adaptive responses, their potential to promote critical thinking remains understudied. In this paper, we fill such a gap and present a
Externí odkaz:
http://arxiv.org/abs/2409.05511
Autor:
Wu, Jianchang, Torresi, Luca, Hu, ManMan, Reiser, Patrick, Zhang, Jiyun, Rocha-Ortiz, Juan S., Wang, Luyao, Xie, Zhiqiang, Zhang, Kaicheng, Park, Byung-wook, Barabash, Anastasia, Zhao, Yicheng, Luo, Junsheng, Wang, Yunuo, Lüer, Larry, Deng, Lin-Long, Hauch, Jens A., Seok, Sang Il, Friederich, Pascal, Brabec, Christoph J.
The inverse design of tailored organic molecules for specific optoelectronic devices of high complexity holds an enormous potential, but has not yet been realized1,2. The complexity and literally infinite diversity of conjugated molecular structures
Externí odkaz:
http://arxiv.org/abs/2407.00729
Autor:
Warne, David J., Crossman, Kerryn, Heron, Grace E. M., Sharp, Jesse A., Jin, Wang, Wu, Paul Pao-Yen, Simpson, Matthew J., Mengersen, Kerrie, Ortiz, Juan-Carlos
Coral reefs are increasingly subjected to major disturbances threatening the health of marine ecosystems. Substantial research underway to develop intervention strategies that assist reefs in recovery from, and resistance to, inevitable future climat
Externí odkaz:
http://arxiv.org/abs/2406.19591
Autor:
Lou, Andrés, Pérez-Ortiz, Juan Antonio, Sánchez-Martínez, Felipe, Sánchez-Cartagena, Víctor M.
Publikováno v:
2024.naacl-long.156
The Mayan languages comprise a language family with an ancient history, millions of speakers, and immense cultural value, that, nevertheless, remains severely underrepresented in terms of resources and global exposure. In this paper we develop, curat
Externí odkaz:
http://arxiv.org/abs/2404.07673
Autor:
Sánchez-Cartagena, Víctor M., Esplà-Gomis, Miquel, Pérez-Ortiz, Juan Antonio, Sánchez-Martínez, Felipe
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 46, Issue: 2, February 2024)
When the amount of parallel sentences available to train a neural machine translation is scarce, a common practice is to generate new synthetic training samples from them. A number of approaches have been proposed to produce synthetic parallel senten
Externí odkaz:
http://arxiv.org/abs/2401.16086
This paper studies the effects of word-level linguistic annotations in under-resourced neural machine translation, for which there is incomplete evidence in the literature. The study covers eight language pairs, different training corpus sizes, two a
Externí odkaz:
http://arxiv.org/abs/2401.16078
Autor:
Wu, Jianchang, Zhang, Jiyun, Hu, Manman, Reiser, Patrick, Torresi, Luca, Friederich, Pascal, Lahn, Leopold, Kasian, Olga, Guldi, Dirk M., Pérez-Ojeda, M. Eugenia, Barabash, Anastasia, Rocha-Ortiz, Juan S., Zhao, Yicheng, Xie, Zhiqiang, Luo, Junsheng, Wang, Yunuo, Seok, Sang Il, Hauch, Jens A., Brabec, Christoph J.
Publikováno v:
J. Am. Chem. Soc. 2023, 145, 30, 1651-16525
High-throughput synthesis of solution-processable structurally variable small-molecule semiconductors is both an opportunity and a challenge. A large number of diverse molecules provide a possibility for quick material discovery and machine learning
Externí odkaz:
http://arxiv.org/abs/2305.07867
Autor:
Alvarez, Pedro D., Ortiz, Juan
We present analytical solutions for homogenous and isotropic spaces of the supersymmetric Chern-Simons model with matter in the adjoint representation. The configurations that we found correspond to a gravitating spinor content and torsion is also pr
Externí odkaz:
http://arxiv.org/abs/2208.07897
Autor:
Sánchez-Cartagena, Víctor M., Esplà-Gomis, Miquel, Pérez-Ortiz, Juan Antonio, Sánchez-Martínez, Felipe
In the context of neural machine translation, data augmentation (DA) techniques may be used for generating additional training samples when the available parallel data are scarce. Many DA approaches aim at expanding the support of the empirical data
Externí odkaz:
http://arxiv.org/abs/2109.03645
Autor:
Labraña, Pedro, Ortiz, Juan
The study of Emergent Universe models is based on the assumption that the universe emerged from a past eternal Einstein Static (ES) state towards an inflationary phase and then evolves into a hot big bang era. These models are appealing since they pr
Externí odkaz:
http://arxiv.org/abs/2108.09524