Zobrazeno 1 - 10
of 36 041
pro vyhledávání: '"P. A. Dinesh"'
Autor:
Josephine Thirumagal Sivashanakar, Rajendra Surenthirakumaran, Nalini Sathyakumar, P. A. Dinesh Coonghe
Publikováno v:
Journal of the College of Community Physicians, Vol 30, Iss 2 (2024)
Introduction: Behavioural problems of adolescents, such as anger, impulsivity, hyperactivity and emotional problems is a cross-cutting issue among all communities, religions and cultures around the world. An influx of internet, social media, alcohol
Externí odkaz:
https://doaj.org/article/c0a1593bc5ca47748836ede81ea25782
The field of text-to-audio generation has seen significant advancements, and yet the ability to finely control the acoustic characteristics of generated audio remains under-explored. In this paper, we introduce a novel yet simple approach to generate
Externí odkaz:
http://arxiv.org/abs/2412.09789
Multigrid methods are asymptotically optimal algorithms ideal for large-scale simulations. But, they require making numerous algorithmic choices that significantly influence their efficiency. Unlike recent approaches that learn optimal multigrid comp
Externí odkaz:
http://arxiv.org/abs/2412.08186
Multigrid methods despite being known to be asymptotically optimal algorithms, depend on the careful selection of their individual components for efficiency. Also, they are mostly restricted to standard cycle types like V-, F-, and W-cycles. We use g
Externí odkaz:
http://arxiv.org/abs/2412.05852
In an era of widespread influence of Natural Language Processing (NLP), there have been multiple research efforts to supplant traditional manual coding techniques with automated systems capable of generating solutions autonomously. With rapid researc
Externí odkaz:
http://arxiv.org/abs/2412.05749
Large Language Models (LLMs) have recently demonstrated impressive few-shot learning capabilities through in-context learning (ICL). However, ICL performance is highly dependent on the choice of few-shot demonstrations, making the selection of the mo
Externí odkaz:
http://arxiv.org/abs/2412.05710
Building generalist agents that can rapidly adapt to new environments is a key challenge for deploying AI in the digital and real worlds. Is scaling current agent architectures the most effective way to build generalist agents? We propose a novel app
Externí odkaz:
http://arxiv.org/abs/2412.04759
The main purpose of this paper is to present the generalization of the inequalities between the modulus of the polar derivative and the polynomial itself, depending on consideration of the zeros inside and outside of a closed disk and the extremal co
Externí odkaz:
http://arxiv.org/abs/2412.04176
Autor:
Ghosal, Soumya Suvra, Chakraborty, Souradip, Singh, Vaibhav, Guan, Tianrui, Wang, Mengdi, Beirami, Ahmad, Huang, Furong, Velasquez, Alvaro, Manocha, Dinesh, Bedi, Amrit Singh
With the widespread deployment of Multimodal Large Language Models (MLLMs) for visual-reasoning tasks, improving their safety has become crucial. Recent research indicates that despite training-time safety alignment, these models remain vulnerable to
Externí odkaz:
http://arxiv.org/abs/2411.18688
Autor:
Hashmi, Sarim, Lugo, Juan, Elsayed, Abdelrahman, Saggurthi, Dinesh, Elseiagy, Mohammed, Nurkamal, Alikhan, Walia, Jaskaran, Maani, Fadillah Adamsyah, Yaqub, Mohammad
Identifying key pathological features in brain MRIs is crucial for the long-term survival of glioma patients. However, manual segmentation is time-consuming, requiring expert intervention and is susceptible to human error. Therefore, significant rese
Externí odkaz:
http://arxiv.org/abs/2411.15872