Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Alghamdi, Emad A."'
Autor:
Longpre, Shayne, Mahari, Robert, Lee, Ariel, Lund, Campbell, Oderinwale, Hamidah, Brannon, William, Saxena, Nayan, Obeng-Marnu, Naana, South, Tobin, Hunter, Cole, Klyman, Kevin, Klamm, Christopher, Schoelkopf, Hailey, Singh, Nikhil, Cherep, Manuel, Anis, Ahmad, Dinh, An, Chitongo, Caroline, Yin, Da, Sileo, Damien, Mataciunas, Deividas, Misra, Diganta, Alghamdi, Emad, Shippole, Enrico, Zhang, Jianguo, Materzynska, Joanna, Qian, Kun, Tiwary, Kush, Miranda, Lester, Dey, Manan, Liang, Minnie, Hamdy, Mohammed, Muennighoff, Niklas, Ye, Seonghyeon, Kim, Seungone, Mohanty, Shrestha, Gupta, Vipul, Sharma, Vivek, Chien, Vu Minh, Zhou, Xuhui, Li, Yizhi, Xiong, Caiming, Villa, Luis, Biderman, Stella, Li, Hanlin, Ippolito, Daphne, Hooker, Sara, Kabbara, Jad, Pentland, Sandy
General-purpose artificial intelligence (AI) systems are built on massive swathes of public web data, assembled into corpora such as C4, RefinedWeb, and Dolma. To our knowledge, we conduct the first, large-scale, longitudinal audit of the consent pro
Externí odkaz:
http://arxiv.org/abs/2407.14933
Autor:
Lee, Mina, Gero, Katy Ilonka, Chung, John Joon Young, Shum, Simon Buckingham, Raheja, Vipul, Shen, Hua, Venugopalan, Subhashini, Wambsganss, Thiemo, Zhou, David, Alghamdi, Emad A., August, Tal, Bhat, Avinash, Choksi, Madiha Zahrah, Dutta, Senjuti, Guo, Jin L. C., Hoque, Md Naimul, Kim, Yewon, Knight, Simon, Neshaei, Seyed Parsa, Sergeyuk, Agnia, Shibani, Antonette, Shrivastava, Disha, Shroff, Lila, Stark, Jessi, Sterman, Sarah, Wang, Sitong, Bosselut, Antoine, Buschek, Daniel, Chang, Joseph Chee, Chen, Sherol, Kreminski, Max, Park, Joonsuk, Pea, Roy, Rho, Eugenia H., Shen, Shannon Zejiang, Siangliulue, Pao
In our era of rapid technological advancement, the research landscape for writing assistants has become increasingly fragmented across various research communities. We seek to address this challenge by proposing a design space as a structured way to
Externí odkaz:
http://arxiv.org/abs/2403.14117
Autor:
Alghamdi, Emad A., Masoud, Reem I., Alnuhait, Deema, Alomairi, Afnan Y., Ashraf, Ahmed, Zaytoon, Mohamed
The swift progress and widespread acceptance of artificial intelligence (AI) systems highlight a pressing requirement to comprehend both the capabilities and potential risks associated with AI. Given the linguistic complexity, cultural richness, and
Externí odkaz:
http://arxiv.org/abs/2403.09017
Generative artificial intelligence (GenAI) has ushered in a new era for storytellers, providing a powerful tool to ignite creativity and explore uncharted narrative territories. As technology continues to advance, the synergy between human creativity
Externí odkaz:
http://arxiv.org/abs/2403.01575
Autor:
Singh, Shivalika, Vargus, Freddie, Dsouza, Daniel, Karlsson, Börje F., Mahendiran, Abinaya, Ko, Wei-Yin, Shandilya, Herumb, Patel, Jay, Mataciunas, Deividas, OMahony, Laura, Zhang, Mike, Hettiarachchi, Ramith, Wilson, Joseph, Machado, Marina, Moura, Luisa Souza, Krzemiński, Dominik, Fadaei, Hakimeh, Ergün, Irem, Okoh, Ifeoma, Alaagib, Aisha, Mudannayake, Oshan, Alyafeai, Zaid, Chien, Vu Minh, Ruder, Sebastian, Guthikonda, Surya, Alghamdi, Emad A., Gehrmann, Sebastian, Muennighoff, Niklas, Bartolo, Max, Kreutzer, Julia, Üstün, Ahmet, Fadaee, Marzieh, Hooker, Sara
Datasets are foundational to many breakthroughs in modern artificial intelligence. Many recent achievements in the space of natural language processing (NLP) can be attributed to the finetuning of pre-trained models on a diverse set of tasks that ena
Externí odkaz:
http://arxiv.org/abs/2402.06619
Neural machine translation (NMT) has shown impressive performance when trained on large-scale corpora. However, generic NMT systems have demonstrated poor performance on out-of-domain translation. To mitigate this issue, several domain adaptation met
Externí odkaz:
http://arxiv.org/abs/2309.12863
Autor:
Altaher, Yousef, Fadel, Ali, Alotaibi, Mazen, Alyazidi, Mazen, Al-Mutairi, Mishari, Aldhbuiub, Mutlaq, Mosaibah, Abdulrahman, Rezk, Abdelrahman, Alhendi, Abdulrazzaq, Shal, Mazen Abo, Alghamdi, Emad A., Alshaibani, Maged S., Zakraoui, Jezia, Mohammed, Wafaa, Gaanoun, Kamel, Elmadani, Khalid N., Ghaleb, Mustafa, Tazi, Nouamane, Alharbi, Raed, Masoud, Maraim, Alyafeai, Zaid
Masader (Alyafeai et al., 2021) created a metadata structure to be used for cataloguing Arabic NLP datasets. However, developing an easy way to explore such a catalogue is a challenging task. In order to give the optimal experience for users and rese
Externí odkaz:
http://arxiv.org/abs/2208.00932
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