Zobrazeno 1 - 10
of 11 618
pro vyhledávání: '"A Rakshit"'
Autor:
Huang, Chubin, Rakshit, Abhishek, Janka, Gianluca, Salman, Zaher, Suter, Andreas, Prokscha, Thomas, Frandsen, Benjamin A., Kalcheim, Yoav
The coupling between structural, electronic and magnetic degrees of freedom across the metal-insulator transition in V2O3 makes it hard to determine the main driving mechanism behind the transition. Specifically, the role of magnetism has been debate
Externí odkaz:
http://arxiv.org/abs/2410.23030
Statistical Inference in High-dimensional Poisson Regression with Applications to Mediation Analysis
Autor:
Rakshit, Prabrisha, Guo, Zijian
Large-scale datasets with count outcome variables are widely present in various applications, and the Poisson regression model is among the most popular models for handling count outcomes. This paper considers the high-dimensional sparse Poisson regr
Externí odkaz:
http://arxiv.org/abs/2410.20671
We introduce Shakti, a 2.5 billion parameter language model specifically optimized for resource-constrained environments such as edge devices, including smartphones, wearables, and IoT systems. Shakti combines high-performance NLP with optimized effi
Externí odkaz:
http://arxiv.org/abs/2410.11331
Autor:
Rakshit, Arghya
We prove a pointwise $C^{2,\,\alpha}$ estimate for the potential of the optimal transport map in the case that the densities are only close to a constant in a certain $L^p$ sense. To do so we use the variational approach recently developed by Goldman
Externí odkaz:
http://arxiv.org/abs/2410.06230
Autor:
Pandey, Shivangi, Rakshit, Suvendu, Chand, Krishan, Stalin, C. S., Cho, Hojin, Woo, Jong-Hak, Jalan, Priyanka, Mandal, Amit Kumar, Omar, Amitesh, Jose, Jincen, Gupta, Archana
Understanding the origins of massive black hole seeds and their co-evolution with their host galaxy requires studying intermediate-mass black holes (IMBHs) and estimating their mass. However, measuring the mass of these IMBHs is challenging due to th
Externí odkaz:
http://arxiv.org/abs/2409.16844
Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of Human Responses in Dialogue
Autor:
Ivey, Jonathan, Kumar, Shivani, Liu, Jiayu, Shen, Hua, Rakshit, Sushrita, Raju, Rohan, Zhang, Haotian, Ananthasubramaniam, Aparna, Kim, Junghwan, Yi, Bowen, Wright, Dustin, Israeli, Abraham, Møller, Anders Giovanni, Zhang, Lechen, Jurgens, David
Studying and building datasets for dialogue tasks is both expensive and time-consuming due to the need to recruit, train, and collect data from study participants. In response, much recent work has sought to use large language models (LLMs) to simula
Externí odkaz:
http://arxiv.org/abs/2409.08330
Instrumental variables are a popular study design for the estimation of treatment effects in the presence of unobserved confounders. In the canonical instrumental variables design, the instrument is a binary variable. In many settings, however, the i
Externí odkaz:
http://arxiv.org/abs/2409.07350
Autor:
Mukherjee, Soham, Dixit, Yash, Srivastava, Naman, Joy, Joel D, Olikara, Rohan, Sinha, Koesha, E, Swarup, Ramesh, Rakshit
The integration of fine-scale multispectral imagery with deep learning models has revolutionized land use and land cover (LULC) classification. However, the atmospheric effects present in Top-of-Atmosphere sensor measured Digital Number values must b
Externí odkaz:
http://arxiv.org/abs/2409.05494
Autor:
Shukla, Shashank K., Rakshit, Gobinda
Consider a non-linear operator equation $x - K(x) = f$, where $f$ is given and $K$ is a Urysohn integral operator with Green's function type kernel defined on $L^\infty [0, 1]$. We apply methods of approximation based on interpolatory projections (wh
Externí odkaz:
http://arxiv.org/abs/2409.01784
Catastrophic forgetting makes neural network models unstable when learning visual domains consecutively. The neural network model drifts to catastrophic forgetting-induced low performance of previously learnt domains when training with new domains. W
Externí odkaz:
http://arxiv.org/abs/2409.00530