Zobrazeno 1 - 10
of 23 903
pro vyhledávání: '"P. P. Murthy"'
Autor:
Kokane, Shirley, Zhu, Ming, Awalgaonkar, Tulika, Zhang, Jianguo, Hoang, Thai, Prabhakar, Akshara, Liu, Zuxin, Lan, Tian, Yang, Liangwei, Tan, Juntao, Murthy, Rithesh, Yao, Weiran, Liu, Zhiwei, Niebles, Juan Carlos, Wang, Huan, Heinecke, Shelby, Xiong, Caiming, Savarese, Silivo
Evaluating the output of Large Language Models (LLMs) is one of the most critical aspects of building a performant compound AI system. Since the output from LLMs propagate to downstream steps, identifying LLM errors is crucial to system performance.
Externí odkaz:
http://arxiv.org/abs/2411.13547
Autor:
Shah, Haritya, Guddati, Murthy
Motivated by elastography that utilizes tissue mechanical properties as biomarkers for liver disease, and the eventual objective of providing explicit links between histology and bulk mechanical properties, we develop a micromechanical modeling appro
Externí odkaz:
http://arxiv.org/abs/2411.13530
Tissue viscoelasticity is becoming an increasingly useful biomarker beyond elasticity and can theoretically be estimated using shear wave elastography (SWE), by inverting the propagation and attenuation characteristics of shear waves. Estimating visc
Externí odkaz:
http://arxiv.org/abs/2411.11572
Autor:
van der Brugge, Vincent, Pollefeys, Marc, Tenenbaum, Joshua B., Tewari, Ayush, Jatavallabhula, Krishna Murthy
Reconstructing compositional 3D representations of scenes, where each object is represented with its own 3D model, is a highly desirable capability in robotics and augmented reality. However, most existing methods rely heavily on strong appearance pr
Externí odkaz:
http://arxiv.org/abs/2411.11196
Does learning of task-relevant representations stop when behavior stops changing? Motivated by recent theoretical advances in machine learning and the intuitive observation that human experts continue to learn from practice even after mastery, we hyp
Externí odkaz:
http://arxiv.org/abs/2411.03541
Autor:
Verma, Sshubam, Khan, Mohammed Safi Ur Rahman, Kumar, Vishwajeet, Murthy, Rudra, Sen, Jaydeep
Evaluating Large Language Models (LLMs) in low-resource and linguistically diverse languages remains a significant challenge in NLP, particularly for languages using non-Latin scripts like those spoken in India. Existing benchmarks predominantly focu
Externí odkaz:
http://arxiv.org/abs/2411.02538
The Ultra Violet Imaging Telescope (UVIT) onboard India's first dedicated multiwavelength satellite \textit{AstroSat} observed a significant fraction of the sky in the ultraviolet with a spatial resolution of 1.4\arcsec. We present a catalog of the p
Externí odkaz:
http://arxiv.org/abs/2411.01809
Autor:
Liu, Zhiwei, Yao, Weiran, Zhang, Jianguo, Murthy, Rithesh, Yang, Liangwei, Liu, Zuxin, Lan, Tian, Zhu, Ming, Tan, Juntao, Kokane, Shirley, Hoang, Thai, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
We introduce the Principled Reasoning and Acting (PRAct) framework, a novel method for learning and enforcing action principles from trajectory data. Central to our approach is the use of text gradients from a reflection and optimization engine to de
Externí odkaz:
http://arxiv.org/abs/2410.18528
The performance of a text-to-speech (TTS) synthesis model depends on various factors, of which the quality of the training data is of utmost importance. Millions of data are collected around the globe for various languages, but resources for Indian l
Externí odkaz:
http://arxiv.org/abs/2410.14197
This paper compares scale-invariant (SIFT) and scale-variant (ORB) feature detection methods, alongside our novel feature detector, IntFeat, specifically applied to lunar imagery. We evaluate these methods using low (128x128) and high-resolution (102
Externí odkaz:
http://arxiv.org/abs/2410.11118