Zobrazeno 1 - 10
of 2 293
pro vyhledávání: '"WANG, Yuxiang"'
High-frequency trading (HFT) represents a pivotal and intensely competitive domain within the financial markets. The velocity and accuracy of data processing exert a direct influence on profitability, underscoring the significance of this field. The
Externí odkaz:
http://arxiv.org/abs/2412.01062
Question answering on free-form tables (a.k.a. TableQA) is a challenging task because of the flexible structure and the complex schema of tables. Recent studies use Large Language Models (LLMs) for this task, exploiting their capability in understand
Externí odkaz:
http://arxiv.org/abs/2410.12846
Autor:
Huang, Zifeng, Yang, Yunfan, Sheng, Da, Li, Hui, Wang, Yuxiang, Sun, Zixuan, Li, Ming, Wang, Runsheng, Huang, Ru, Cheng, Zhe
High-purity cubic silicon carbide possesses the second-highest thermal conductivity among large-scale crystals, surpassed only by diamond, making it crucial for practical applications of thermal management. Recent theoretical studies predict that hea
Externí odkaz:
http://arxiv.org/abs/2409.18843
Autor:
Wang, Yuxiang, Yan, Xiao, Jin, Shiyu, Xu, Quanqing, Yang, Chuanhui, Zhu, Yuanyuan, Hu, Chuang, Du, Bo, Jiang, Jiawei
Text-attributed graph (TAG) is an important type of graph structured data with text descriptions for each node. Few- and zero-shot node classification on TAGs have many applications in fields such as academia and social networks. However, the two tas
Externí odkaz:
http://arxiv.org/abs/2409.00727
Autor:
Geng, Yuxia, Zhu, Runkai, Chen, Jiaoyan, Chen, Jintai, Chen, Zhuo, Chen, Xiang, Xu, Can, Wang, Yuxiang, Xu, Xiaoliang
Disentanglement of visual features of primitives (i.e., attributes and objects) has shown exceptional results in Compositional Zero-shot Learning (CZSL). However, due to the feature divergence of an attribute (resp. object) when combined with differe
Externí odkaz:
http://arxiv.org/abs/2408.09786
Autor:
Yin, Weibo, Zhang, Jianan, Jia, Fengdong, Wang, Yuhan, Wang, Yuxiang, Hao, Jianhai, Cui, Yue, Liu, Ya, Zhong, Zhiping
We propose and demonstrate a novel method for measuring the polarization direction of a microwave electric field in a single measurement using a Rydberg atom-based mixer with two orthogonally polarized local microwave electric fields. Furthermore, in
Externí odkaz:
http://arxiv.org/abs/2408.00988
Autor:
Yuan, Zilong, Tang, Zechen, Tao, Honggeng, Gong, Xiaoxun, Chen, Zezhou, Wang, Yuxiang, Li, He, Li, Yang, Xu, Zhiming, Sun, Minghui, Zhao, Boheng, Wang, Chong, Duan, Wenhui, Xu, Yong
Deep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in deep-learning density functional theory (DFT) Hamiltonian matrices, they
Externí odkaz:
http://arxiv.org/abs/2407.14379
Autor:
Tang, Zechen, Zou, Nianlong, Li, He, Wang, Yuxiang, Yuan, Zilong, Tao, Honggeng, Li, Yang, Chen, Zezhou, Zhao, Boheng, Sun, Minghui, Jiang, Hong, Duan, Wenhui, Xu, Yong
The combination of deep learning and ab initio materials calculations is emerging as a trending frontier of materials science research, with deep-learning density functional theory (DFT) electronic structure being particularly promising. In this work
Externí odkaz:
http://arxiv.org/abs/2406.17561
Autor:
Wang, Yuxiang, Li, Yang, Tang, Zechen, Li, He, Yuan, Zilong, Tao, Honggeng, Zou, Nianlong, Bao, Ting, Liang, Xinghao, Chen, Zezhou, Xu, Shanghua, Bian, Ce, Xu, Zhiming, Wang, Chong, Si, Chen, Duan, Wenhui, Xu, Yong
Realizing large materials models has emerged as a critical endeavor for materials research in the new era of artificial intelligence, but how to achieve this fantastic and challenging objective remains elusive. Here, we propose a feasible pathway to
Externí odkaz:
http://arxiv.org/abs/2406.10536
Autor:
Ma, Jianwen, Meng, Xianghao, Zhang, Binhua, Wang, Yuxiang, Mou, Yicheng, Lin, Wenting, Dai, Yannan, Chen, Luqiu, Wang, Haonan, Wu, Haoqi, Gu, Jiaming, Wang, Jiayu, Du, Yuhan, Liu, Chunsen, Shi, Wu, Yang, Zhenzhong, Tian, Bobo, Miao, Lin, Zhou, Peng, Duan, Chun-Gang, Xu, Changsong, Yuan, Xiang, Zhang, Cheng
Publikováno v:
Science Bulletin 69(13), 2042-2049 (2024)
Owing to the outstanding properties provided by nontrivial band topology, topological phases of matter are considered as a promising platform towards low-dissipation electronics, efficient spin-charge conversion, and topological quantum computation.
Externí odkaz:
http://arxiv.org/abs/2405.03966