Zobrazeno 1 - 10
of 236
pro vyhledávání: '"Ahmed, Ahmed M"'
Autor:
Smith, C. Estelle, Shiekh, Kylee, Cooreman, Hayden, Rahman, Sharfi, Zhu, Yifei, Siam, Md Kamrul, Ivanitskiy, Michael, Ahmed, Ahmed M., Hallinan, Michael, Grisak, Alexander, Fierro, Gabe
Because of the rapid development and increasing public availability of Generative Artificial Intelligence (GenAI) models and tools, educational institutions and educators must immediately reckon with the impact of students using GenAI. There is limit
Externí odkaz:
http://arxiv.org/abs/2411.11166
Reinforcement Learning from Human Feedback (RLHF) has enabled significant advancements within language modeling for powerful, instruction-following models. However, the alignment of these models remains a pressing challenge as the policy tends to ove
Externí odkaz:
http://arxiv.org/abs/2406.01013
Autor:
Vidgen, Bertie, Agrawal, Adarsh, Ahmed, Ahmed M., Akinwande, Victor, Al-Nuaimi, Namir, Alfaraj, Najla, Alhajjar, Elie, Aroyo, Lora, Bavalatti, Trupti, Bartolo, Max, Blili-Hamelin, Borhane, Bollacker, Kurt, Bomassani, Rishi, Boston, Marisa Ferrara, Campos, Siméon, Chakra, Kal, Chen, Canyu, Coleman, Cody, Coudert, Zacharie Delpierre, Derczynski, Leon, Dutta, Debojyoti, Eisenberg, Ian, Ezick, James, Frase, Heather, Fuller, Brian, Gandikota, Ram, Gangavarapu, Agasthya, Gangavarapu, Ananya, Gealy, James, Ghosh, Rajat, Goel, James, Gohar, Usman, Goswami, Sujata, Hale, Scott A., Hutiri, Wiebke, Imperial, Joseph Marvin, Jandial, Surgan, Judd, Nick, Juefei-Xu, Felix, Khomh, Foutse, Kailkhura, Bhavya, Kirk, Hannah Rose, Klyman, Kevin, Knotz, Chris, Kuchnik, Michael, Kumar, Shachi H., Kumar, Srijan, Lengerich, Chris, Li, Bo, Liao, Zeyi, Long, Eileen Peters, Lu, Victor, Luger, Sarah, Mai, Yifan, Mammen, Priyanka Mary, Manyeki, Kelvin, McGregor, Sean, Mehta, Virendra, Mohammed, Shafee, Moss, Emanuel, Nachman, Lama, Naganna, Dinesh Jinenhally, Nikanjam, Amin, Nushi, Besmira, Oala, Luis, Orr, Iftach, Parrish, Alicia, Patlak, Cigdem, Pietri, William, Poursabzi-Sangdeh, Forough, Presani, Eleonora, Puletti, Fabrizio, Röttger, Paul, Sahay, Saurav, Santos, Tim, Scherrer, Nino, Sebag, Alice Schoenauer, Schramowski, Patrick, Shahbazi, Abolfazl, Sharma, Vin, Shen, Xudong, Sistla, Vamsi, Tang, Leonard, Testuggine, Davide, Thangarasa, Vithursan, Watkins, Elizabeth Anne, Weiss, Rebecca, Welty, Chris, Wilbers, Tyler, Williams, Adina, Wu, Carole-Jean, Yadav, Poonam, Yang, Xianjun, Zeng, Yi, Zhang, Wenhui, Zhdanov, Fedor, Zhu, Jiacheng, Liang, Percy, Mattson, Peter, Vanschoren, Joaquin
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safety risks of AI systems that use chat-tuned language models. We introdu
Externí odkaz:
http://arxiv.org/abs/2404.12241
In imitation and reinforcement learning, the cost of human supervision limits the amount of data that robots can be trained on. An aspirational goal is to construct self-improving robots: robots that can learn and improve on their own, from autonomou
Externí odkaz:
http://arxiv.org/abs/2303.01488
Autor:
Ahmed, Ahmed M. M.1, Radic, Abeer A.2, Saad, Mohammed A. A.1, Mohamed, Mahmoud Fakeer3 mahmoudfakeer555@gmail.com
Publikováno v:
Assiut Journal of Agricultural Sciences. Oct2024, Vol. 55 Issue 4, p106-114. 9p.
We aim to present and analyze a nonlinear nonlocal reverse-spacetime fifth-order scalar Sasa-Satsuma equation, based on a nonlocal $5 \times 5$ matrix AKNS spectral problem. Starting from a nonlocal matrix AKNS spectral problem, local and nonlocal sy
Externí odkaz:
http://arxiv.org/abs/2207.01179
Publikováno v:
In Waste Management 1 January 2025 191:135-146
Autor:
Ahmed, Ahmed M. G., Adjiri, Alle
In this paper, we are going to solve nonlinear nonlocal reverse-time six-component six-order AKNS system. We used reverse-time reduction to reduce the coupled system to an integrable six-order NLS-type equation. Starting from the spectral problem of
Externí odkaz:
http://arxiv.org/abs/2201.06738
A highly desirable property of a reinforcement learning (RL) agent -- and a major difficulty for deep RL approaches -- is the ability to generalize policies learned on a few tasks over a high-dimensional observation space to similar tasks not seen du
Externí odkaz:
http://arxiv.org/abs/2106.02193
Autor:
Ahmed, Ahmed M.1 (AUTHOR) ahmedelkb@yahoo.com, Saied, Ahmed I.2 (AUTHOR) ahmed.abosaied@fsc.bu.edu.eg, Ali, Maha3 (AUTHOR) mayoali@kku.edu.sa, Zakarya, Mohammed4 (AUTHOR) mzibrahim@kku.edu.sa, Rezk, Haytham M.1 (AUTHOR) haythamrezk@azhar.edu.eg
Publikováno v:
Symmetry (20738994). Mar2024, Vol. 16 Issue 3, p288. 20p.