Zobrazeno 1 - 10
of 996
pro vyhledávání: '"Zhao Yuxiang"'
In recent years, deep learning, powered by neural networks, has achieved widespread success in solving high-dimensional problems, particularly those with low-dimensional feature structures. This success stems from their ability to identify and learn
Externí odkaz:
http://arxiv.org/abs/2412.05144
Autor:
Hao, Jing, Zhao, Yuxiang, Chen, Song, Sun, Yanpeng, Chen, Qiang, Zhang, Gang, Yao, Kun, Ding, Errui, Wang, Jingdong
Multimodal Large Language Models (MLLMs) have shown promise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities. However, they heavily depend on high-quality data in the Supervised Fine-Tuning (SFT) p
Externí odkaz:
http://arxiv.org/abs/2409.13540
We report on the first global analysis of transverse momentum dependent helicity distributions of the proton. The analysis is performed at next-to-leading order with the evolution factor at next-to-next-to-leading-logarithmic accuracy. Nonzero signal
Externí odkaz:
http://arxiv.org/abs/2409.08110
Autor:
Zhao, Yuxiang, Hu, Jiangyong, Liu, Ruijuan, Gao, Ruochen, Li, Yiming, Zhang, Xiao, Zhu, Huanfeng, Wu, Saijun
Acousto-optical modulation (AOM) is a powerful and widely used technique for rapidly controlling the frequency, phase, intensity, and direction of light. Based on Bragg diffraction, AOMs typically exhibit moderate diffraction efficiency, often less t
Externí odkaz:
http://arxiv.org/abs/2408.15051
Fragmentation functions (FFs) are essential non-perturbative QCD inputs for predicting hadron production cross sections in high energy scatterings. In this study, we present a joint determination of FFs for light charged hadrons through a global anal
Externí odkaz:
http://arxiv.org/abs/2407.04422
In this research, we conduct a global QCD analysis of fragmentation functions (FFs) for neutral pions ($\pi^0$), neutral kaons ($K_S^0$), and eta mesons ($\eta$), utilizing world data of single inclusive hadron production in $e^+e^-$ annihilation inv
Externí odkaz:
http://arxiv.org/abs/2404.11527
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2024
IR drop on the power delivery network (PDN) is closely related to PDN's configuration and cell current consumption. As the integrated circuit (IC) design is growing larger, dynamic IR drop simulation becomes computationally unaffordable and machine l
Externí odkaz:
http://arxiv.org/abs/2403.18569
We present a global analysis of the trans-helicity worm-gear distribution function, $g_{1T}^\perp$, by fitting the longitudinal-transverse double spin asymmetry data of the semi-inclusive deep inelastic scattering. The analysis is performed within th
Externí odkaz:
http://arxiv.org/abs/2403.12795
Autor:
Chen, Lei, Chen, Yiqi, Chu, Zhufei, Fang, Wenji, Ho, Tsung-Yi, Huang, Ru, Huang, Yu, Khan, Sadaf, Li, Min, Li, Xingquan, Li, Yu, Liang, Yun, Liu, Jinwei, Liu, Yi, Lin, Yibo, Luo, Guojie, Shi, Zhengyuan, Sun, Guangyu, Tsaras, Dimitrios, Wang, Runsheng, Wang, Ziyi, Wei, Xinming, Xie, Zhiyao, Xu, Qiang, Xue, Chenhao, Yan, Junchi, Yang, Jun, Yu, Bei, Yuan, Mingxuan, Young, Evangeline F. Y., Zeng, Xuan, Zhang, Haoyi, Zhang, Zuodong, Zhao, Yuxiang, Zhen, Hui-Ling, Zheng, Ziyang, Zhu, Binwu, Zhu, Keren, Zou, Sunan
Within the Electronic Design Automation (EDA) domain, AI-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domain
Externí odkaz:
http://arxiv.org/abs/2403.07257
In this work, we investigate the problem of simultaneous blind demixing and super-resolution. Leveraging the subspace assumption regarding unknown point spread functions, this problem can be reformulated as a low-rank matrix demixing problem. We prop
Externí odkaz:
http://arxiv.org/abs/2401.11805