Zobrazeno 1 - 10
of 9 235
pro vyhledávání: '"ZHENG, HAO"'
Autor:
Liu, Yufeng, Li, Zonglin, Jiang, Shudan, Li, Min, Gu, Yu, Liu, Kai, Shen, Qia, Liu, Liang, Liu, Xiaoxue, Guan, Dandan, Li, Yaoyi, Zheng, Hao, Liu, Canhua, Watanabe, Kenji, Taniguchi, Takashi, Jia, Jinfeng, Li, Tingxin, Chen, Guorui, Liu, Jianpeng, Li, Can, Shi, Zhiwen, Wang, Shiyong
Rhombohedral graphene (RG) has emerged as a promising platform for exploring exotic quantum phenomena, such as quantum magnetism, unconventional superconductivity, and fractional quantum anomalous Hall effects. Despite its potential, atomic-scale inv
Externí odkaz:
http://arxiv.org/abs/2412.06476
Recently, there has been a growing interest in leveraging Large Language Models for Verilog code generation. However, the current quality of the generated Verilog code remains suboptimal. This is largely due to the absence of well-defined, well-organ
Externí odkaz:
http://arxiv.org/abs/2412.06947
InfiniteWorld: A Unified Scalable Simulation Framework for General Visual-Language Robot Interaction
Autor:
Ren, Pengzhen, Li, Min, Luo, Zhen, Song, Xinshuai, Chen, Ziwei, Liufu, Weijia, Yang, Yixuan, Zheng, Hao, Xu, Rongtao, Huang, Zitong, Ding, Tongsheng, Xie, Luyang, Zhang, Kaidong, Fu, Changfei, Liu, Yang, Lin, Liang, Zheng, Feng, Liang, Xiaodan
Realizing scaling laws in embodied AI has become a focus. However, previous work has been scattered across diverse simulation platforms, with assets and models lacking unified interfaces, which has led to inefficiencies in research. To address this,
Externí odkaz:
http://arxiv.org/abs/2412.05789
Dark photon is one of the promising candidates of light dark matter and could be detected by using its interaction with standard model particles via kinetic mixings. Here, we propose a feasible approach to detect the dark photons by nondestructively
Externí odkaz:
http://arxiv.org/abs/2412.00786
Autor:
He, Zihong, Lin, Weizhe, Zheng, Hao, Zhang, Fan, Jones, Matt, Aitchison, Laurence, Xu, Xuhai, Liu, Miao, Kristensson, Per Ola, Shen, Junxiao
With the rapid advancement of AI systems, their abilities to store, retrieve, and utilize information over the long term - referred to as long-term memory - have become increasingly significant. These capabilities are crucial for enhancing the perfor
Externí odkaz:
http://arxiv.org/abs/2411.00489
Autor:
Shen, Qia, Chen, Jiaxin, Rong, Bin, Rong, Yaqi, Chen, Hongliang, Zhao, Tieyang, Duan, Xianfa, Guan, Dandan, Wang, Shiyong, Li, Yaoyi, Zheng, Hao, Liu, Xiaoxue, Qiu, Xuepeng, Chen, Jingsheng, Cong, Longqing, Li, Tingxin, Zhong, Ruidan, Liu, Canhua, Yang, Yumeng, Liu, Liang, Jia, Jinfeng
Nonlinear Hall effect (NLHE) offers a novel means of uncovering symmetry and topological properties in quantum materials, holding promise for exotic (opto)electronic applications such as microwave rectification and THz detection. The BCD-independent
Externí odkaz:
http://arxiv.org/abs/2410.22156
Autor:
Liu, Chen, Tao, Shengdan, Wang, Guanyong, Chen, Hongyuan, Xia, Bing, Yang, Hao, Liu, Xiaoxue, Liu, Liang, Li, Yaoyi, Wang, Shiyong, Zheng, Hao, Liu, Canhua, Guan, Dandan, Lu, Yunhao, Jia, Jin-feng
We have investigated the structures and electronic properties of ultra-thin Bi(110) films grown on an s-wave superconductor substrate using low-temperature scanning tunneling microscopy and spectroscopy. Remarkably, our experimental results validate
Externí odkaz:
http://arxiv.org/abs/2410.19369
Autor:
Wang, Yan, Zhou, Jie, Fan, Xing-Yan, Hao, Ze-Yan, Li, Jia-Kun, Liu, Zheng-Hao, Sun, Kai, Xu, Jin-Shi, Chen, Jing-Ling, Li, Chuan-Feng, Guo, Guang-Can
As the fundamental tool in quantum information science, the uncertainty principle is essential for manifesting nonclassical properties of quantum systems. Plenty of efforts on the uncertainty principle with two observables have been achieved, making
Externí odkaz:
http://arxiv.org/abs/2410.05925
Test-time adaptation (TTA) has emerged as a promising paradigm to handle the domain shifts at test time for medical images from different institutions without using extra training data. However, existing TTA solutions for segmentation tasks suffer fr
Externí odkaz:
http://arxiv.org/abs/2410.01573
Secure training, while protecting the confidentiality of both data and model weights, typically incurs significant training overhead. Traditional Fully Homomorphic Encryption (FHE)-based non-inter-active training models are heavily burdened by comput
Externí odkaz:
http://arxiv.org/abs/2409.16675