Zobrazeno 1 - 10
of 5 688
pro vyhledávání: '"Kumaravel A"'
Publikováno v:
Journal of Natural Fibers, Vol 19, Iss 15, Pp 10447-10461 (2022)
The natural fiber composites are emerging as replacement materials in wide engineering fields. In this work, banana, sisal, and banana-sisal fibers of three different fiber lengths namely 3 mm, 5 mm, and 7 mm are used as reinforcements in the epoxy m
Externí odkaz:
https://doaj.org/article/99f1c92e37cb48dcb1373024b02998d2
Autor:
Numan, Nels, Rajaram, Shwetha, Kumaravel, Balasaravanan Thoravi, Marquardt, Nicolai, Wilson, Andrew D.
There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR) applications. However, today's models produce artificial environments, falling short of supporting collaborative tasks that benefit from incorporating the
Externí odkaz:
http://arxiv.org/abs/2409.13926
Autor:
Basu, Kinjal, Abdelaziz, Ibrahim, Bradford, Kelsey, Crouse, Maxwell, Kate, Kiran, Kumaravel, Sadhana, Goyal, Saurabh, Munawar, Asim, Rizk, Yara, Wang, Xin, Lastras, Luis, Kapanipathi, Pavan
Autonomous agent applications powered by large language models (LLMs) have recently risen to prominence as effective tools for addressing complex real-world tasks. At their core, agentic workflows rely on LLMs to plan and execute the use of tools and
Externí odkaz:
http://arxiv.org/abs/2409.03797
Autor:
Abdelaziz, Ibrahim, Basu, Kinjal, Agarwal, Mayank, Kumaravel, Sadhana, Stallone, Matthew, Panda, Rameswar, Rizk, Yara, Bhargav, GP, Crouse, Maxwell, Gunasekara, Chulaka, Ikbal, Shajith, Joshi, Sachin, Karanam, Hima, Kumar, Vineet, Munawar, Asim, Neelam, Sumit, Raghu, Dinesh, Sharma, Udit, Soria, Adriana Meza, Sreedhar, Dheeraj, Venkateswaran, Praveen, Unuvar, Merve, Cox, David, Roukos, Salim, Lastras, Luis, Kapanipathi, Pavan
Large language models (LLMs) have recently shown tremendous promise in serving as the backbone to agentic systems, as demonstrated by their performance in multi-faceted, challenging benchmarks like SWE-Bench and Agent-Bench. However, to realize the t
Externí odkaz:
http://arxiv.org/abs/2407.00121
BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AI
Autor:
Rajaram, Shwetha, Numan, Nels, Kumaravel, Balasaravanan Thoravi, Marquardt, Nicolai, Wilson, Andrew D.
Today's video-conferencing tools support a rich range of professional and social activities, but their generic meeting environments cannot be dynamically adapted to align with distributed collaborators' needs. To enable end-user customization, we dev
Externí odkaz:
http://arxiv.org/abs/2403.13947
Autor:
Basu, Kinjal, Abdelaziz, Ibrahim, Chaudhury, Subhajit, Dan, Soham, Crouse, Maxwell, Munawar, Asim, Kumaravel, Sadhana, Muthusamy, Vinod, Kapanipathi, Pavan, Lastras, Luis A.
There is a growing need for Large Language Models (LLMs) to effectively use tools and external Application Programming Interfaces (APIs) to plan and complete tasks. As such, there is tremendous interest in methods that can acquire sufficient quantiti
Externí odkaz:
http://arxiv.org/abs/2402.15491
Publikováno v:
FME Transactions, Vol 45, Iss 1, Pp 83-88 (2017)
The wear Behaviour of LM 25 reinforced with nano Al2O3, a nanocomposite with increased wear resistance is investigated. Strength and Stiffness is manufactured by Stir casting. Four different specimens of reinforced nanocomposite have been manufacture
Externí odkaz:
https://doaj.org/article/b8201b7019434480ab88745dd79f182e
Publikováno v:
Informatics in Medicine Unlocked, Vol 15, Iss , Pp - (2019)
Application of computational tools in medical science can assist physicians with analysis of disease. Herein, prediction based on a subset featured approach with the Siddha medical treatment dataset is utilized for peptic ulcers, using a simple linea
Externí odkaz:
https://doaj.org/article/a8d053e2ff69485782385c40f566f138
Autor:
Crouse, Maxwell, Abdelaziz, Ibrahim, Astudillo, Ramon, Basu, Kinjal, Dan, Soham, Kumaravel, Sadhana, Fokoue, Achille, Kapanipathi, Pavan, Roukos, Salim, Lastras, Luis
Autonomous, goal-driven agents powered by LLMs have recently emerged as promising tools for solving challenging problems without the need for task-specific finetuned models that can be expensive to procure. Currently, the design and implementation of
Externí odkaz:
http://arxiv.org/abs/2310.08535
The sliding window approach provides an elegant way to handle contexts of sizes larger than the Transformer's input window, for tasks like language modeling. Here we extend this approach to the sequence-to-sequence task of document parsing. For this,
Externí odkaz:
http://arxiv.org/abs/2305.17273