Zobrazeno 1 - 10
of 356 808
pro vyhledávání: '"Ko AT"'
Autor:
Dogiel, Vladimir A., Ko, Chung-Ming
Publikováno v:
Universe 2024, 10(11), 424
Two enigmatic gamma-ray features in the Galactic central region, known as Fermi Bubbles (FBs), were found from Fermi-LAT data. An energy release (e.g., by tidal disruption events in the Galactic center, GC), generates a cavity with a shock that expan
Externí odkaz:
http://arxiv.org/abs/2411.14916
Autor:
Ko, Minsung, Jeon, Myoungwon, Choi, Yumi, Kallivayalil, Nitya, Sohn, Sangmo Tony, Besla, Gurtina, Richstein, Hannah, Fu, Sal Wanying, Jeong, Tae Bong, Shin, Jihye
Reproducing the physical characteristics of ultra-faint dwarf galaxies (UFDs) in cosmological simulations is challenging, particularly with respect to stellar metallicity and galaxy size. To investigate these difficulties in detail, we conduct high-r
Externí odkaz:
http://arxiv.org/abs/2411.14683
This study investigates language models' generative capabilities in tool-use dialogs. We categorize the models' outputs in tool-use dialogs into four distinct types: Tool Call, Answer Completion, Slot Question, and Relevance Detection, which serve as
Externí odkaz:
http://arxiv.org/abs/2411.14054
Autor:
Song, Sang Yong, Hua, Chengyun, Halász, Gábor B., Ko, Wonhee, Yan, Jiaqiang, Lawrie, Benjamin J., Maksymovych, Petro
To realize braiding of vortex lines and understand the basic properties of the energy landscape for vortex motion, precise manipulation of superconducting vortices on the nanoscale is required. Here, we reveal that a localized trapping potential powe
Externí odkaz:
http://arxiv.org/abs/2411.11724
Federated Learning (FL) enables collaborative model training across distributed devices while preserving local data privacy, making it ideal for mobile and embedded systems. However, the decentralized nature of FL also opens vulnerabilities to model
Externí odkaz:
http://arxiv.org/abs/2411.12220
Robot swarms offer significant potential for inspecting diverse infrastructure, ranging from bridges to space stations. However, effective inspection requires accurate robot localization, which demands substantial computational resources and limits p
Externí odkaz:
http://arxiv.org/abs/2411.09493
In this study, we propose an ensemble learning framework for electroencephalogram-based overt speech classification, leveraging denoising diffusion probabilistic models with varying convolutional kernel sizes. The ensemble comprises three models with
Externí odkaz:
http://arxiv.org/abs/2411.09302
Autor:
Joo, Hyungjin, Jee, M. James, Kim, Juhan, Lee, Jaehyun, Ko, Jongwan, Park, Changbom, Shin, Jihye, Snaith, Owain, Pichon, Christophe, Gibson, Brad, Kim, Yonghwi
We investigate the formation history of intrahalo light (IHL) using the high-resolution (~1 kpc), large-scale (~Gpc) cosmological hydrodynamical simulation, Horizon Run 5 (HR5). IHL particles are identified by carefully considering both their binding
Externí odkaz:
http://arxiv.org/abs/2411.08117
The collection of speech data carried out in Sociolinguistics has the potential to enhance large language models due to its quality and representativeness. In this paper, we examine the ethical considerations associated with the gathering and dissemi
Externí odkaz:
http://arxiv.org/abs/2411.07512
Autor:
Aoki, Ko
We construct a locally profinite set of cardinality $\aleph_{\omega}$ with infinitely many first cohomology classes of which any distinct finite product does not vanish. Building on this, we construct the first example of a nondescendable faithfully
Externí odkaz:
http://arxiv.org/abs/2411.05995