Zobrazeno 1 - 10
of 1 828
pro vyhledávání: '"Wang, Lijie"'
Autor:
Zhao, Liang, Wei, Tianwen, Zeng, Liang, Cheng, Cheng, Yang, Liu, Cheng, Peng, Wang, Lijie, Li, Chenxia, Wu, Xuejie, Zhu, Bo, Gan, Yimeng, Hu, Rui, Yan, Shuicheng, Fang, Han, Zhou, Yahui
We introduce LongSkywork, a long-context Large Language Model (LLM) capable of processing up to 200,000 tokens. We provide a training recipe for efficiently extending context length of LLMs. We identify that the critical element in enhancing long-con
Externí odkaz:
http://arxiv.org/abs/2406.00605
Autor:
Dong, Peng, Wang, Lijie, Zhang, Guanqun, He, Jiadian, Zhang, Yiwen, Ding, Yifan, Zeng, Xiaohui, Wang, Jinghui, Zhou, Xiang, Wu, Yueshen, Li, Wei, Li, Jun
Nonreciprocal charge transport in heterostructural superconductors exhibits appealing quantum physical phenomena and holds the promising potential for superconducting circuits applications. Realizing a nonreciprocity is, however, fundamentally and te
Externí odkaz:
http://arxiv.org/abs/2401.13072
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), pp.1-10, 2024
In recent years, analog circuits have received extensive attention and are widely used in many emerging applications. The high demand for analog circuits necessitates shorter circuit design cycles. To achieve the desired performance and specification
Externí odkaz:
http://arxiv.org/abs/2312.14405
Autor:
Wang, Lijie, Nughays, Razan, Yin, Jun, Shih, Chun-Hua, Guo, Tsung-Fang, Mohammed, Omar F., Chergui, Majed
Using ultrafast broad-band transient absorption (TA) spectroscopy of photo-excited MAPbBr3 thin films with probe continua in the visible and the mid-to-deep-UV ranges, we capture the ultrafast gap renormalization at the fundamental gap situated at th
Externí odkaz:
http://arxiv.org/abs/2312.06480
As commonly-used methods for debiasing natural language understanding (NLU) models, dataset refinement approaches heavily rely on manual data analysis, and thus maybe unable to cover all the potential biased features. In this paper, we propose IBADR,
Externí odkaz:
http://arxiv.org/abs/2311.00292
Autor:
Wei, Tianwen, Zhao, Liang, Zhang, Lichang, Zhu, Bo, Wang, Lijie, Yang, Haihua, Li, Biye, Cheng, Cheng, Lü, Weiwei, Hu, Rui, Li, Chenxia, Yang, Liu, Luo, Xilin, Wu, Xuejie, Liu, Lunan, Cheng, Wenjun, Cheng, Peng, Zhang, Jianhao, Zhang, Xiaoyu, Lin, Lei, Wang, Xiaokun, Ma, Yutuan, Dong, Chuanhai, Sun, Yanqi, Chen, Yifu, Peng, Yongyi, Liang, Xiaojuan, Yan, Shuicheng, Fang, Han, Zhou, Yahui
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3.2 trillion tokens drawn from both English and Chinese texts. This bilingual foundation model is the most extensively trained and
Externí odkaz:
http://arxiv.org/abs/2310.19341
Autor:
Yang, Liu, Yang, Haihua, Cheng, Wenjun, Lin, Lei, Li, Chenxia, Chen, Yifu, Liu, Lunan, Pan, Jianfei, Wei, Tianwen, Li, Biye, Zhao, Liang, Wang, Lijie, Zhu, Bo, Li, Guoliang, Wu, Xuejie, Luo, Xilin, Hu, Rui
Large language models (LLMs) have shown great potential to solve varieties of natural language processing (NLP) tasks, including mathematical reasoning. In this work, we present SkyMath, a large language model for mathematics with 13 billion paramete
Externí odkaz:
http://arxiv.org/abs/2310.16713
Current Transformer-based natural language understanding (NLU) models heavily rely on dataset biases, while failing to handle real-world out-of-distribution (OOD) instances. Many methods have been proposed to deal with this issue, but they ignore the
Externí odkaz:
http://arxiv.org/abs/2306.01907
Autor:
Wang, Lijie1,2 (AUTHOR) wlj@hrbust.edu.cn, Zhu, Xianwen1,2 (AUTHOR) 2220600066@stu.hrbust.edu.cn, Li, Ziyi1,2 (AUTHOR) 2420600019@stu.hrbust.edu.cn, Li, Shuchao1,2 (AUTHOR)
Publikováno v:
Sensors (14248220). Sep2024, Vol. 24 Issue 17, p5694. 22p.
Autor:
Wang, Xiaoni, Wang, Lijie, Liu, Yixin, Chen, Fan, Gao, Wanpeng, Wu, Yu, Xu, Zulei, Peng, Wei, Wang, Zhen, Di, Zengfeng, Li, Wei, Mu, Gang, Lin, Zhirong
Publikováno v:
Phys. Rev. B 107, 094509 (2023)
Quantum Griffiths singularity (QGS), which is closely correlated with the quenched disorder, is characterized by the divergence of the dynamical critical exponent and the presence of activated scaling behavior. Typically such a quantum phenomenon is
Externí odkaz:
http://arxiv.org/abs/2211.05393