Zobrazeno 1 - 10
of 3 543
pro vyhledávání: '"Karanam A"'
We consider the problem of independently, in a disentangled fashion, controlling the outputs of text-to-image diffusion models with color and style attributes of a user-supplied reference image. We present the first training-free, test-time-only meth
Externí odkaz:
http://arxiv.org/abs/2409.02429
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 32, Iss , Pp 101061- (2022)
This work demonstrates Automatic Generation Control (AGC) of two and three area reheat thermal system with nonlinearities. A Two Degree of Freedom Optimal Fuzzy Aided PID (2DOF OFAPID) controller is applied in all areas as secondary controller. The p
Externí odkaz:
https://doaj.org/article/6dfef92ba75d4ed6a279adcff08c9acf
Referring Expression Segmentation (RES) aims to provide a segmentation mask of the target object in an image referred to by the text (i.e., referring expression). Existing methods require large-scale mask annotations. Moreover, such approaches do not
Externí odkaz:
http://arxiv.org/abs/2407.02389
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
We consider the problem of customizing text-to-image diffusion models with user-supplied reference images. Given new prompts, the existing methods can capture the key concept from the reference images but fail to align the generated image with the pr
Externí odkaz:
http://arxiv.org/abs/2406.18893
Autor:
Rangwani, Harsh, Agarwal, Aishwarya, Kulkarni, Kuldeep, Babu, R. Venkatesh, Karanam, Srikrishna
Text-to-image generation from large generative models like Stable Diffusion, DALLE-2, etc., have become a common base for various tasks due to their superior quality and extensive knowledge bases. As image composition and generation are creative proc
Externí odkaz:
http://arxiv.org/abs/2406.10197
Autor:
Bhargav, G P Shrivatsa, Neelam, Sumit, Sharma, Udit, Ikbal, Shajith, Sreedhar, Dheeraj, Karanam, Hima, Joshi, Sachindra, Dhoolia, Pankaj, Garg, Dinesh, Croutwater, Kyle, Qi, Haode, Wayne, Eric, Murdock, J William
We present an approach to build Large Language Model (LLM) based slot-filling system to perform Dialogue State Tracking in conversational assistants serving across a wide variety of industry-grade applications. Key requirements of this system include
Externí odkaz:
http://arxiv.org/abs/2406.08848
Autor:
Chitti Ramarao, Busakala Vamsi Krishna, Karanam Aravind Swamy, Pothireddi Teja, P.H.J. Venkatesh
Publikováno v:
E3S Web of Conferences, Vol 391, p 01044 (2023)
Metal cylindrical shells are widely used to store and transport highly hazardous chemicals and used as pressure vessels and pipelines. These structures can be subjected to explosive loads to accidents, terrorism, or military actions. The design of th
Externí odkaz:
https://doaj.org/article/2f386415233946269143a2ef5c38b16f
Probabilistic Circuits (PCs) have emerged as an efficient framework for representing and learning complex probability distributions. Nevertheless, the existing body of research on PCs predominantly concentrates on data-driven parameter learning, ofte
Externí odkaz:
http://arxiv.org/abs/2405.02413
Recent advancements in deep learning have demonstrated remarkable performance comparable to human capabilities across various supervised computer vision tasks. However, the prevalent assumption of having an extensive pool of training data encompassin
Externí odkaz:
http://arxiv.org/abs/2405.01040