Zobrazeno 1 - 10
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pro vyhledávání: '"Aly, Ahmed"'
Autor:
Le, Trang, Lazar, Daniel, Kim, Suyoun, Jiang, Shan, Le, Duc, Sagar, Adithya, Livshits, Aleksandr, Aly, Ahmed, Shrivastava, Akshat
Spoken Language Understanding (SLU) is a critical component of voice assistants; it consists of converting speech to semantic parses for task execution. Previous works have explored end-to-end models to improve the quality and robustness of SLU model
Externí odkaz:
http://arxiv.org/abs/2406.07823
Autor:
Elhoushi, Mostafa, Shrivastava, Akshat, Liskovich, Diana, Hosmer, Basil, Wasti, Bram, Lai, Liangzhen, Mahmoud, Anas, Acun, Bilge, Agarwal, Saurabh, Roman, Ahmed, Aly, Ahmed A, Chen, Beidi, Wu, Carole-Jean
We present LayerSkip, an end-to-end solution to speed-up inference of large language models (LLMs). First, during training we apply layer dropout, with low dropout rates for earlier layers and higher dropout rates for later layers, and an early exit
Externí odkaz:
http://arxiv.org/abs/2404.16710
Autor:
Ravi, Sahithya, Huber, Patrick, Shrivastava, Akshat, Sagar, Aditya, Aly, Ahmed, Shwartz, Vered, Einolghozati, Arash
The emergence of Large Language Models (LLMs) has brought to light promising language generation capabilities, particularly in performing tasks like complex reasoning and creative writing. Consequently, distillation through imitation of teacher respo
Externí odkaz:
http://arxiv.org/abs/2402.18113
Autor:
Mohammed Mustafa, Rumesa Batul, Mohmed Isaqali Karobari, Hadi Mohammed Alamri, Abdulaziz Abdulwahed, Ahmed A. Almokhatieb, Qamar Hashem, Abdullah Alsakaker, Mohammad Khursheed Alam, Hany Mohamed Aly Ahmed
Publikováno v:
BMC Oral Health, Vol 24, Iss 1, Pp 1-29 (2024)
Abstract Introduction Root canal treatment procedures require a thorough understanding of root and canal anatomy. The purpose of this systematic review was to examine the morphological differences of teeth root and their canals assessed using cone-be
Externí odkaz:
https://doaj.org/article/ff62e54a181247bbbdab31c50a737f7a
Autor:
Aly Ahmed, Ahmed Mohammed1 drabdrabo2017@gmail.com, Al--Zayat, Ahmed Abd Elfattah2, Abdelsamei, Magdy Mohammed2, Allam, Muhammad Maher2, Mohamed, Mohamed Mohsen2
Publikováno v:
Zagazig University Medical Journal. May/Jun2024, Vol. 30 Issue 3, p927-934. 8p.
Due to the ubiquity of mobile phones and location-detection devices, location data is being generated in very large volumes. Queries and operations that are performed on location data warrant the use of database systems. Despite that, location data i
Externí odkaz:
http://arxiv.org/abs/2206.09520
Autor:
Rafiqul Islam, Md Refat Readul Islam, Toru Tanaka, Mohammad Khursheed Alam, Hany Mohamed Aly Ahmed, Hidehiko Sano
Publikováno v:
Japanese Dental Science Review, Vol 59, Iss , Pp 48-61 (2023)
The aim of direct pulp capping (DPC) is to promote pulp healing and mineralized tissue barrier formation by placing a dental biomaterial directly over the exposed pulp. Successful application of this approach avoids the need for further and more exte
Externí odkaz:
https://doaj.org/article/cba3c5f6037c401d859a2f5b0d54a224
Autor:
Shrivastava, Akshat, Desai, Shrey, Gupta, Anchit, Elkahky, Ali, Livshits, Aleksandr, Zotov, Alexander, Aly, Ahmed
Task-oriented semantic parsing models have achieved strong results in recent years, but unfortunately do not strike an appealing balance between model size, runtime latency, and cross-domain generalizability. We tackle this problem by introducing sce
Externí odkaz:
http://arxiv.org/abs/2202.00901
Autor:
Xing, Lu, Lee, Eric, An, Tong, Chu, Bo-Cheng, Mahmood, Ahmed, Aly, Ahmed M., Wang, Jianguo, Aref, Walid G.
Waves of misery is a phenomenon where spikes of many node splits occur over short periods of time in tree indexes. Waves of misery negatively affect the performance of tree indexes in insertion-heavy workloads.Waves of misery have been first observed
Externí odkaz:
http://arxiv.org/abs/2112.13174
Autor:
Sethi, Pooja, Savenkov, Denis, Arabshahi, Forough, Goetz, Jack, Tolliver, Micaela, Scheffer, Nicolas, Kabul, Ilknur, Liu, Yue, Aly, Ahmed
Improving the quality of Natural Language Understanding (NLU) models, and more specifically, task-oriented semantic parsing models, in production is a cumbersome task. In this work, we present a system called AutoNLU, which we designed to scale the N
Externí odkaz:
http://arxiv.org/abs/2110.06384