Zobrazeno 1 - 10
of 7 414
pro vyhledávání: '"Sirui An"'
Autor:
Can Gong, Minhan Mi, Yuwei Zhou, Pengfei Wang, Yilin Chen, Jielong Liu, Yutong Han, Sirui An, Siyin Guo, Meng Zhang, Qing Zhu, Mei Yang, Xiaohua Ma, Yue Hao
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 11, Pp 72-77 (2023)
In this work, high performance InAlN/GaN HEMT based on the n+GaN regrown ohmic contact with n+GaN contact ledge structure is proposed. The regrown ohmic contact of InAlN/GaN HEMT is formed by MBE n+GaN regrowth and self-stopping etching, which makes
Externí odkaz:
https://doaj.org/article/77231092cf96498cb56106544ab5e5fe
Evaluation metric of visual captioning is important yet not thoroughly explored. Traditional metrics like BLEU, METEOR, CIDEr, and ROUGE often miss semantic depth, while trained metrics such as CLIP-Score, PAC-S, and Polos are limited in zero-shot sc
Externí odkaz:
http://arxiv.org/abs/2412.13647
Autor:
Gao, Dongxin, Fan, Daojin, Zha, Chen, Bei, Jiahao, Cai, Guoqing, Cai, Jianbin, Cao, Sirui, Zeng, Xiangdong, Chen, Fusheng, Chen, Jiang, Chen, Kefu, Chen, Xiawei, Chen, Xiqing, Chen, Zhe, Chen, Zhiyuan, Chen, Zihua, Chu, Wenhao, Deng, Hui, Deng, Zhibin, Ding, Pei, Ding, Xun, Ding, Zhuzhengqi, Dong, Shuai, Dong, Yupeng, Fan, Bo, Fu, Yuanhao, Gao, Song, Ge, Lei, Gong, Ming, Gui, Jiacheng, Guo, Cheng, Guo, Shaojun, Guo, Xiaoyang, He, Tan, Hong, Linyin, Hu, Yisen, Huang, He-Liang, Huo, Yong-Heng, Jiang, Tao, Jiang, Zuokai, Jin, Honghong, Leng, Yunxiang, Li, Dayu, Li, Dongdong, Li, Fangyu, Li, Jiaqi, Li, Jinjin, Li, Junyan, Li, Junyun, Li, Na, Li, Shaowei, Li, Wei, Li, Yuhuai, Li, Yuan, Liang, Futian, Liang, Xuelian, Liao, Nanxing, Lin, Jin, Lin, Weiping, Liu, Dailin, Liu, Hongxiu, Liu, Maliang, Liu, Xinyu, Liu, Xuemeng, Liu, Yancheng, Lou, Haoxin, Ma, Yuwei, Meng, Lingxin, Mou, Hao, Nan, Kailiang, Nie, Binghan, Nie, Meijuan, Ning, Jie, Niu, Le, Peng, Wenyi, Qian, Haoran, Rong, Hao, Rong, Tao, Shen, Huiyan, Shen, Qiong, Su, Hong, Su, Feifan, Sun, Chenyin, Sun, Liangchao, Sun, Tianzuo, Sun, Yingxiu, Tan, Yimeng, Tan, Jun, Tang, Longyue, Tu, Wenbing, Wan, Cai, Wang, Jiafei, Wang, Biao, Wang, Chang, Wang, Chen, Wang, Chu, Wang, Jian, Wang, Liangyuan, Wang, Rui, Wang, Shengtao, Wang, Xinzhe, Wei, Zuolin, Wei, Jiazhou, Wu, Dachao, Wu, Gang, Wu, Jin, Wu, Shengjie, Wu, Yulin, Xie, Shiyong, Xin, Lianjie, Xu, Yu, Xue, Chun, Yan, Kai, Yang, Weifeng, Yang, Xinpeng, Yang, Yang, Ye, Yangsen, Ye, Zhenping, Ying, Chong, Yu, Jiale, Yu, Qinjing, Yu, Wenhu, Zhan, Shaoyu, Zhang, Feifei, Zhang, Haibin, Zhang, Kaili, Zhang, Pan, Zhang, Wen, Zhang, Yiming, Zhang, Yongzhuo, Zhang, Lixiang, Zhao, Guming, Zhao, Peng, Zhao, Xianhe, Zhao, Xintao, Zhao, Youwei, Zhao, Zhong, Zheng, Luyuan, Zhou, Fei, Zhou, Liang, Zhou, Na, Zhou, Naibin, Zhou, Shifeng, Zhou, Shuang, Zhou, Zhengxiao, Zhu, Chengjun, Zhu, Qingling, Zou, Guihong, Zou, Haonan, Zhang, Qiang, Lu, Chao-Yang, Peng, Cheng-Zhi, Zhu, XiaoBo, Pan, Jian-Wei
In the relentless pursuit of quantum computational advantage, we present a significant advancement with the development of Zuchongzhi 3.0. This superconducting quantum computer prototype, comprising 105 qubits, achieves high operational fidelities, w
Externí odkaz:
http://arxiv.org/abs/2412.11924
Autor:
Dang, Yunkai, Huang, Kaichen, Huo, Jiahao, Yan, Yibo, Huang, Sirui, Liu, Dongrui, Gao, Mengxi, Zhang, Jie, Qian, Chen, Wang, Kun, Liu, Yong, Shao, Jing, Xiong, Hui, Hu, Xuming
The rapid development of Artificial Intelligence (AI) has revolutionized numerous fields, with large language models (LLMs) and computer vision (CV) systems driving advancements in natural language understanding and visual processing, respectively. T
Externí odkaz:
http://arxiv.org/abs/2412.02104
Autor:
Yin, Shukang, Fu, Chaoyou, Zhao, Sirui, Shen, Yunhang, Ge, Chunjiang, Yang, Yan, Long, Zuwei, Dai, Yuhan, Xu, Tong, Sun, Xing, He, Ran, Shan, Caifeng, Chen, Enhong
The success of Multimodal Large Language Models (MLLMs) in the image domain has garnered wide attention from the research community. Drawing on previous successful experiences, researchers have recently explored extending the success to the video und
Externí odkaz:
http://arxiv.org/abs/2411.19951
Large language models (LLMs) have shown remarkable capability in natural language tasks, yet debate persists on whether they truly comprehend deep structure (i.e., core semantics) or merely rely on surface structure (e.g., presentation format). Prior
Externí odkaz:
http://arxiv.org/abs/2411.19456
Autor:
Fu, Chaoyou, Zhang, Yi-Fan, Yin, Shukang, Li, Bo, Fang, Xinyu, Zhao, Sirui, Duan, Haodong, Sun, Xing, Liu, Ziwei, Wang, Liang, Shan, Caifeng, He, Ran
As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language Models (MLLMs) have garnered increased attention from both industry and academia. Building upon pre-trained LLMs, this family of models further develops mult
Externí odkaz:
http://arxiv.org/abs/2411.15296
We propose a method, HotSpot, for optimizing neural signed distance functions, based on a relation between the solution of a screened Poisson equation and the distance function. Existing losses such as the eikonal loss cannot guarantee the recovered
Externí odkaz:
http://arxiv.org/abs/2411.14628
Complex Cyber-Physical System (CPS) such as Unmanned Aerial System (UAS) got rapid development these years, but also became vulnerable to GPS spoofing, packets injection, buffer-overflow and other malicious attacks. Ensuring the behaviors of UAS alwa
Externí odkaz:
http://arxiv.org/abs/2411.07741
Large Language Models (LLMs) are proficient at retrieving single facts from extended contexts, yet they struggle with tasks requiring the simultaneous retrieval of multiple facts, especially during generation. This paper identifies a novel "lost-in-t
Externí odkaz:
http://arxiv.org/abs/2410.21012