Zobrazeno 1 - 10
of 697 204
pro vyhledávání: '"A, Rao"'
Social media is a great source of data for users reporting information and regarding their health and how various things have had an effect on them. This paper presents various approaches using Transformers and Large Language Models and their ensembl
Externí odkaz:
http://arxiv.org/abs/2410.15998
Autor:
Chen, Bowen, Shang, Zaixi, Chung, Jae Won, Lerner, David, Robitza, Werner, Rao, Rakesh Rao Ramachandra, Raake, Alexander, Bovik, Alan C.
Demand for streaming services, including satellite, continues to exhibit unprecedented growth. Internet Service Providers find themselves at the crossroads of technological advancements and rising customer expectations. To stay relevant and competiti
Externí odkaz:
http://arxiv.org/abs/2410.13952
A framework of finite-velocity model based Boltzmann equation has been developed for convection-diffusion equations. These velocities are kept flexible and adjusted to control numerical diffusion. A flux difference splitting based kinetic scheme is t
Externí odkaz:
http://arxiv.org/abs/2409.20101
Autor:
Ferland, Matthew, Rao, Varun Nagaraj, Arora, Arushi, van der Poel, Drew, Luu, Michael, Huynh, Randy, Reiber, Freddy, Ossman, Sandra, Poulsen, Seth, Shindler, Michael
Concept inventories are standardized assessments that evaluate student understanding of key concepts within academic disciplines. While prevalent across STEM fields, their development lags for advanced computer science topics like dynamic programming
Externí odkaz:
http://arxiv.org/abs/2411.14655
Autor:
Dong, Yuhao, Liu, Zuyan, Sun, Hai-Long, Yang, Jingkang, Hu, Winston, Rao, Yongming, Liu, Ziwei
Large Language Models (LLMs) demonstrate enhanced capabilities and reliability by reasoning more, evolving from Chain-of-Thought prompting to product-level solutions like OpenAI o1. Despite various efforts to improve LLM reasoning, high-quality long-
Externí odkaz:
http://arxiv.org/abs/2411.14432
The increasing prevalence of cloud-native technologies, particularly containers, has led to the widespread adoption of containerized deployments in data centers. The advancement of deep neural network models has increased the demand for container-bas
Externí odkaz:
http://arxiv.org/abs/2411.13809
Autor:
Ruis, Laura, Mozes, Maximilian, Bae, Juhan, Kamalakara, Siddhartha Rao, Talupuru, Dwarak, Locatelli, Acyr, Kirk, Robert, Rocktäschel, Tim, Grefenstette, Edward, Bartolo, Max
The capabilities and limitations of Large Language Models have been sketched out in great detail in recent years, providing an intriguing yet conflicting picture. On the one hand, LLMs demonstrate a general ability to solve problems. On the other han
Externí odkaz:
http://arxiv.org/abs/2411.12580
MAViS: Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays
Autor:
Rao, Anantha S., Buterakos, Donovan, van Straaten, Barnaby, John, Valentin, Yu, Cécile X., Oosterhout, Stefan D., Stehouwer, Lucas, Scappucci, Giordano, Veldhorst, Menno, Borsoi, Francesco, Zwolak, Justyna P.
Arrays of gate-defined semiconductor quantum dots are among the leading candidates for building scalable quantum processors. High-fidelity initialization, control, and readout of spin qubit registers require exquisite and targeted control over key Ha
Externí odkaz:
http://arxiv.org/abs/2411.12516
Autor:
Rao, P Raghavendra, Vyavahare, Pooja
This work studies the distributed learning process on a network of agents. Agents make partial observation about an unknown hypothesis and iteratively share their beliefs over a set of possible hypotheses with their neighbors to learn the true hypoth
Externí odkaz:
http://arxiv.org/abs/2411.11411
Autor:
Shen, Yueyang, Sudjianto, Agus, R, Arun Prakash, Bhattacharyya, Anwesha, Rao, Maorong, Wang, Yaqun, Vaughan, Joel, Zhou, Nengfeng
We propose and study a minimalist approach towards synthetic tabular data generation. The model consists of a minimalistic unsupervised SparsePCA encoder (with contingent clustering step or log transformation to handle nonlinearity) and XGboost decod
Externí odkaz:
http://arxiv.org/abs/2411.10982