Zobrazeno 1 - 10
of 11 262
pro vyhledávání: '"Hyunsoo An"'
Creating high-quality, large-scale datasets for large language models (LLMs) often relies on resource-intensive, GPU-accelerated models for quality filtering, making the process time-consuming and costly. This dependence on GPUs limits accessibility
Externí odkaz:
http://arxiv.org/abs/2411.11289
Autor:
Kim, Hyunsoo
Recently, urban air mobility (UAM) has attracted attention as an emerging technology that will bring innovation to urban transportation and aviation systems. Since the UAM systems pursue fully autonomous flight without a pilot, wireless communication
Externí odkaz:
http://arxiv.org/abs/2410.17572
Autor:
Park, Chanjun, Ha, Hyunsoo, Kim, Jihoo, Kim, Yungi, Kim, Dahyun, Lee, Sukyung, Yang, Seonghoon
In this paper, we propose the 1 Trillion Token Platform (1TT Platform), a novel framework designed to facilitate efficient data sharing with a transparent and equitable profit-sharing mechanism. The platform fosters collaboration between data contrib
Externí odkaz:
http://arxiv.org/abs/2409.20149
We propose a data-driven viscosity solver based on U-shaped convolutional neural network to predict velocity changes due to viscosity. Our solver takes velocity derivatives, fluid volume, and solid indicator quantities as input. The traditional marke
Externí odkaz:
http://arxiv.org/abs/2409.14653
With the increasing demand for substantial amounts of high-quality data to train large language models (LLMs), efficiently filtering large web corpora has become a critical challenge. For this purpose, KenLM, a lightweight n-gram-based language model
Externí odkaz:
http://arxiv.org/abs/2409.09613
Publikováno v:
J. Phys. D: Appl. Phys. 55, 095001 (2022)
We fabricated a wedge-shaped Pt/Co/Pt device with perpendicular magnetic anisotropy and manifested that the Co magnetization can be solely switched by spin-orbit torque without any magnetic field. Similar to the synaptic weight, we observed that the
Externí odkaz:
http://arxiv.org/abs/2409.06286
Autor:
Kim, Dae-Yun, Berrai, Imane, Suraj, T. S., Roussigne, Yves, Yang, Shuhan, Belmeguenai, Mohamed, Hu, Fanrui, Shi, Guoyi, Tan, Hui Ru, Huang, Jifei, Soumyanarayanan, Anjan, Kim, Kyoung-Whan, Cherif, Salim Mourad, Yang, Hyunsoo
Chiral magnets have garnered significant interest due to the emergence of unique phenomena prohibited in inversion-symmetric magnets. While the equilibrium characteristics of chiral magnets have been extensively explored through the Dzyaloshinskii-Mo
Externí odkaz:
http://arxiv.org/abs/2409.04713
Sequential recommendation aims to predict the next item a user is likely to prefer based on their sequential interaction history. Recently, text-based sequential recommendation has emerged as a promising paradigm that uses pre-trained language models
Externí odkaz:
http://arxiv.org/abs/2409.00702
Few-shot Anomaly Detection (FAD) poses significant challenges due to the limited availability of training samples and the frequent absence of abnormal samples. Previous approaches often rely on annotations or true abnormal samples to improve detectio
Externí odkaz:
http://arxiv.org/abs/2408.13516
We demonstrate that large language models (LLMs) exhibit consistent value orientations despite adopting diverse personas, revealing a persistent inertia in their responses that remains stable across the variety of roles they are prompted to assume. T
Externí odkaz:
http://arxiv.org/abs/2408.09049