Zobrazeno 1 - 10
of 16 669
pro vyhledávání: '"A Majd"'
Autor:
Zayyad, Majd, Adi, Yossi
The integration of retrieval-augmented techniques with LLMs has shown promise in improving performance across various domains. However, their utility in tasks requiring advanced reasoning, such as generating and evaluating mathematical statements and
Externí odkaz:
http://arxiv.org/abs/2412.16689
Autor:
Rodriguez, Pedro Sales, Robinson, John M., Jepsen, Paul Niklas, He, Zhiyang, Duckering, Casey, Zhao, Chen, Wu, Kai-Hsin, Campo, Joseph, Bagnall, Kevin, Kwon, Minho, Karolyshyn, Thomas, Weinberg, Phillip, Cain, Madelyn, Evered, Simon J., Geim, Alexandra A., Kalinowski, Marcin, Li, Sophie H., Manovitz, Tom, Amato-Grill, Jesse, Basham, James I., Bernstein, Liane, Braverman, Boris, Bylinskii, Alexei, Choukri, Adam, DeAngelo, Robert, Fang, Fang, Fieweger, Connor, Frederick, Paige, Haines, David, Hamdan, Majd, Hammett, Julian, Hsu, Ning, Hu, Ming-Guang, Huber, Florian, Jia, Ningyuan, Kedar, Dhruv, Kornjača, Milan, Liu, Fangli, Long, John, Lopatin, Jonathan, Lopes, Pedro L. S., Luo, Xiu-Zhe, Macrì, Tommaso, Marković, Ognjen, Martínez-Martínez, Luis A., Meng, Xianmei, Ostermann, Stefan, Ostroumov, Evgeny, Paquette, David, Qiang, Zexuan, Shofman, Vadim, Singh, Anshuman, Singh, Manuj, Sinha, Nandan, Thoreen, Henry, Wan, Noel, Wang, Yiping, Waxman-Lenz, Daniel, Wong, Tak, Wurtz, Jonathan, Zhdanov, Andrii, Zheng, Laurent, Greiner, Markus, Keesling, Alexander, Gemelke, Nathan, Vuletić, Vladan, Kitagawa, Takuya, Wang, Sheng-Tao, Bluvstein, Dolev, Lukin, Mikhail D., Lukin, Alexander, Zhou, Hengyun, Cantú, Sergio H.
Realizing universal fault-tolerant quantum computation is a key goal in quantum information science. By encoding quantum information into logical qubits utilizing quantum error correcting codes, physical errors can be detected and corrected, enabling
Externí odkaz:
http://arxiv.org/abs/2412.15165
Autor:
Majd, Amir M.
One propounded theory for the presence of chaos in biological neural networks is that it could be involved in discriminating different olfactory stimuli. Inspired by the idea, in this paper, we define the visual ``chaotic perception'' and spell out t
Externí odkaz:
http://arxiv.org/abs/2411.08511
This paper introduces a new method for safety-aware robot learning, focusing on repairing policies using predictive models. Our method combines behavioral cloning with neural network repair in a two-step supervised learning framework. It first learns
Externí odkaz:
http://arxiv.org/abs/2411.04408
Autor:
Kosta, Majd, Amir, Oded
In this study, we investigate and compare formulations for computing shape derivatives in bi-material level-set optimization with precise modeling of the interface. The level-set function is parameterized using B-splines, whose coordinates serve as d
Externí odkaz:
http://arxiv.org/abs/2410.21532
Autor:
Gonzalez-Cuadra, Daniel, Hamdan, Majd, Zache, Torsten V., Braverman, Boris, Kornjaca, Milan, Lukin, Alexander, Cantu, Sergio H., Liu, Fangli, Wang, Sheng-Tao, Keesling, Alexander, Lukin, Mikhail D., Zoller, Peter, Bylinskii, Alexei
Lattice gauge theories (LGTs) describe a broad range of phenomena in condensed matter and particle physics. A prominent example is confinement, responsible for bounding quarks inside hadrons such as protons or neutrons. When quark-antiquark pairs are
Externí odkaz:
http://arxiv.org/abs/2410.16558
Autor:
Ghrear, Majd, McLean, Alasdair G., Korandla, Hima B., Dastgiri, Ferdos, Spooner, Neil J. C., Vahsen, Sven E.
Detecting the topology and direction of low-energy nuclear and electronic recoils is broadly desirable in nuclear and particle physics, with applications in coherent elastic neutrino-nucleus scattering (CE$\nu$NS), astrophysical neutrino measurements
Externí odkaz:
http://arxiv.org/abs/2410.00048
Autor:
Kornjača, Milan, Hu, Hong-Ye, Zhao, Chen, Wurtz, Jonathan, Weinberg, Phillip, Hamdan, Majd, Zhdanov, Andrii, Cantu, Sergio H., Zhou, Hengyun, Bravo, Rodrigo Araiza, Bagnall, Kevin, Basham, James I., Campo, Joseph, Choukri, Adam, DeAngelo, Robert, Frederick, Paige, Haines, David, Hammett, Julian, Hsu, Ning, Hu, Ming-Guang, Huber, Florian, Jepsen, Paul Niklas, Jia, Ningyuan, Karolyshyn, Thomas, Kwon, Minho, Long, John, Lopatin, Jonathan, Lukin, Alexander, Macrì, Tommaso, Marković, Ognjen, Martínez-Martínez, Luis A., Meng, Xianmei, Ostroumov, Evgeny, Paquette, David, Robinson, John, Rodriguez, Pedro Sales, Singh, Anshuman, Sinha, Nandan, Thoreen, Henry, Wan, Noel, Waxman-Lenz, Daniel, Wong, Tak, Wu, Kai-Hsin, Lopes, Pedro L. S., Boger, Yuval, Gemelke, Nathan, Kitagawa, Takuya, Keesling, Alexander, Gao, Xun, Bylinskii, Alexei, Yelin, Susanne F., Liu, Fangli, Wang, Sheng-Tao
Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite this promise, most contemporary quantum methods require significant res
Externí odkaz:
http://arxiv.org/abs/2407.02553
Text segmentation holds paramount importance in the field of Natural Language Processing (NLP). It plays an important role in several NLP downstream tasks like information retrieval and document summarization. In this work, we propose a new solution,
Externí odkaz:
http://arxiv.org/abs/2406.19526
Modern blockchain, such as Ethereum, supports the deployment and execution of so-called smart contracts, autonomous digital programs with significant value of cryptocurrency. Executing smart contracts requires gas costs paid by users, which define th
Externí odkaz:
http://arxiv.org/abs/2406.16244