Zobrazeno 1 - 10
of 33 324
pro vyhledávání: '"Arı, A."'
We present analytical results for the distribution of first return (FR) times of non-backtracking random walks (NBWs) on undirected configuration model networks consisting of $N$ nodes with degree distribution $P(k)$. We focus on the case in which th
Externí odkaz:
http://arxiv.org/abs/2412.12341
Autor:
Pagnoni, Artidoro, Pasunuru, Ram, Rodriguez, Pedro, Nguyen, John, Muller, Benjamin, Li, Margaret, Zhou, Chunting, Yu, Lili, Weston, Jason, Zettlemoyer, Luke, Ghosh, Gargi, Lewis, Mike, Holtzman, Ari, Iyer, Srinivasan
We introduce the Byte Latent Transformer (BLT), a new byte-level LLM architecture that, for the first time, matches tokenization-based LLM performance at scale with significant improvements in inference efficiency and robustness. BLT encodes bytes in
Externí odkaz:
http://arxiv.org/abs/2412.09871
Autor:
Volpert, Carolyn G., Barrentine, Emily M., Bolatto, Alberto D., Brown, Ari, Connors, Jake A., Essinger-Hileman, Thomas, Hess, Larry A., Mikula, Vilem, Stevenson, Thomas R., Switzer, Eric R.
As superconducting kinetic inductance detectors (KIDs) continue to grow in popularity for sensitive sub-mm detection and other applications, there is a drive to advance toward lower loss devices. We present measurements of diagnostic thin film alumin
Externí odkaz:
http://arxiv.org/abs/2412.08811
Estimating uncertainty in Large Language Models (LLMs) is important for properly evaluating LLMs, and ensuring safety for users. However, prior approaches to uncertainty estimation focus on the final answer in generated text, ignoring intermediate st
Externí odkaz:
http://arxiv.org/abs/2412.07961
Autor:
Brill, Ari
Deep neural networks exhibit empirical neural scaling laws, with error decreasing as a power law with increasing model or data size, across a wide variety of architectures, tasks, and datasets. This universality suggests that scaling laws may result
Externí odkaz:
http://arxiv.org/abs/2412.07942
Autor:
Tran, Aaron, Frank, Samuel J., Le, Ari Y., Stanier, Adam J., Wetherton, Blake A., Egedal, Jan, Endrizzi, Douglass A., Harvey, Robert W., Petrov, Yuri V., Qian, Tony M., Sanwalka, Kunal, Viola, Jesse, Forest, Cary B., Zweibel, Ellen G.
The kinetic stability of collisionless, sloshing beam-ion (45{\deg} pitch angle) plasma is studied in a 3D simple magnetic mirror, mimicking the Wisconsin High-temperature superconductor Axisymmetric Mirror (WHAM) experiment. The collisional Fokker-P
Externí odkaz:
http://arxiv.org/abs/2412.04656
Autor:
Austgen, James, Fábrega, Andrés, Kelkar, Mahimna, Vilardell, Dani, Allen, Sarah, Babel, Kushal, Yu, Jay, Juels, Ari
Inherent in the world of cryptocurrency systems and their security models is the notion that private keys, and thus assets, are controlled by individuals or individual entities. We present Liquefaction, a wallet platform that demonstrates the dangero
Externí odkaz:
http://arxiv.org/abs/2412.02634
Active Learning (AL) is a user-interactive approach aimed at reducing annotation costs by selecting the most crucial examples to label. Although AL has been extensively studied for image classification tasks, the specific scenario of interactive imag
Externí odkaz:
http://arxiv.org/abs/2412.02310
The popularity of large language models (LLMs) continues to increase, and LLM-based assistants have become ubiquitous, assisting people of diverse backgrounds in many aspects of life. Significant resources have been invested in the safety of LLMs and
Externí odkaz:
http://arxiv.org/abs/2411.13207
Autor:
Stern, Ari, Viviani, Milo
Runge-Kutta methods are affine equivariant: applying a method before or after an affine change of variables yields the same numerical trajectory. However, for some applications, one would like to perform numerical integration after a quadratic change
Externí odkaz:
http://arxiv.org/abs/2411.12634