Zobrazeno 1 - 10
of 18 861
pro vyhledávání: '"A A Shehata"'
Autor:
Abdelatief, A. Shehata, Renders, A. J., Alqedra, M., Hansen, J. J., Hunger, D., Rippe, L., Walther, A.
We report on experimental investigation of potential high-performance cavity length stabilization using odd-indexed higher-order spatial modes. Schemes based on higher-order modes are particularly useful for micro-cavities that are used for enhanced
Externí odkaz:
http://arxiv.org/abs/2412.00271
Traits are patterns of brain signals and behaviors that are stable over time but differ across individuals, whereas states are phasic patterns that vary over time, are influenced by the environment, yet oscillate around the traits. The quality of a s
Externí odkaz:
http://arxiv.org/abs/2411.12145
Autor:
Saeed, Muhammed, Mohamed, Elgizouli, Mohamed, Mukhtar, Raza, Shaina, Abdul-Mageed, Muhammad, Shehata, Shady
Large language models (LLMs) are widely used but raise ethical concerns due to embedded social biases. This study examines LLM biases against Arabs versus Westerners across eight domains, including women's rights, terrorism, and anti-Semitism and ass
Externí odkaz:
http://arxiv.org/abs/2410.24049
Autor:
Talafha, Bashar, Kadaoui, Karima, Magdy, Samar Mohamed, Habiboullah, Mariem, Chafei, Chafei Mohamed, El-Shangiti, Ahmed Oumar, Zayed, Hiba, tourad, Mohamedou cheikh, Alhamouri, Rahaf, Assi, Rwaa, Alraeesi, Aisha, Mohamed, Hour, Alwajih, Fakhraddin, Mohamed, Abdelrahman, Mekki, Abdellah El, Nagoudi, El Moatez Billah, Saadia, Benelhadj Djelloul Mama, Alsayadi, Hamzah A., Al-Dhabyani, Walid, Shatnawi, Sara, Ech-Chammakhy, Yasir, Makouar, Amal, Berrachedi, Yousra, Jarrar, Mustafa, Shehata, Shady, Berrada, Ismail, Abdul-Mageed, Muhammad
In spite of the recent progress in speech processing, the majority of world languages and dialects remain uncovered. This situation only furthers an already wide technological divide, thereby hindering technological and socioeconomic inclusion. This
Externí odkaz:
http://arxiv.org/abs/2410.04527
Autor:
Beck, Thomas, Baroni, Alessandro, Bennink, Ryan, Buchs, Gilles, Perez, Eduardo Antonio Coello, Eisenbach, Markus, da Silva, Rafael Ferreira, Meena, Muralikrishnan Gopalakrishnan, Gottiparthi, Kalyan, Groszkowski, Peter, Humble, Travis S., Landfield, Ryan, Maheshwari, Ketan, Oral, Sarp, Sandoval, Michael A., Shehata, Amir, Suh, In-Saeng, Zimmer, Christopher
Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era's inherent ext
Externí odkaz:
http://arxiv.org/abs/2408.16159
Reinforcement Learning (RL) algorithms suffer from the dependency on accurately engineered reward functions to properly guide the learning agents to do the required tasks. Preference-based reinforcement learning (PbRL) addresses that by utilizing hum
Externí odkaz:
http://arxiv.org/abs/2408.11943
Autor:
Radwan, Ahmed, Shehata, Mohamed S.
Federated Domain Generalization (FedDG), aims to tackle the challenge of generalizing to unseen domains at test time while catering to the data privacy constraints that prevent centralized data storage from different domains originating at various cl
Externí odkaz:
http://arxiv.org/abs/2407.14792
Medical imaging tasks are very challenging due to the lack of publicly available labeled datasets. Hence, it is difficult to achieve high performance with existing deep-learning models as they require a massive labeled dataset to be trained effective
Externí odkaz:
http://arxiv.org/abs/2407.14784
Achieving domain generalization in medical imaging poses a significant challenge, primarily due to the limited availability of publicly labeled datasets in this domain. This limitation arises from concerns related to data privacy and the necessity fo
Externí odkaz:
http://arxiv.org/abs/2407.14719
Autor:
Doughman, Jad, Afzal, Osama Mohammed, Toyin, Hawau Olamide, Shehata, Shady, Nakov, Preslav, Talat, Zeerak
Recent improvements in the quality of the generations by large language models have spurred research into identifying machine-generated text. Such work often presents high-performing detectors. However, humans and machines can produce text in differe
Externí odkaz:
http://arxiv.org/abs/2406.11073