Zobrazeno 1 - 10
of 9 488
pro vyhledávání: '"Yu, Gang"'
Autor:
Yu, Gang
Publikováno v:
Comptes Rendus. Mathématique, Vol 361, Iss G3, Pp 609-616 (2023)
In this note, we investigate the $L_1$-norms of Barker polynomials and, more generally, Littlewood polynomials over the unit circle, and give improvements to some existing results.
Externí odkaz:
https://doaj.org/article/ea0cfcc72a094a2eb06631da01b9246f
Autor:
Feng, Qian, Zhao, Hanbin, Zhang, Chao, Dong, Jiahua, Ding, Henghui, Jiang, Yu-Gang, Qian, Hui
Incremental Learning (IL) aims to learn deep models on sequential tasks continually, where each new task includes a batch of new classes and deep models have no access to task-ID information at the inference time. Recent vast pre-trained models (PTMs
Externí odkaz:
http://arxiv.org/abs/2407.03813
Autor:
Chen, Jinhui, Dong, Xin, He, Xionghong, Huang, Huanzhong, Liu, Feng, Luo, Xiaofeng, Ma, Yu-Gang, Ruan, Lijuan, Shao, Ming, Shi, Shusu, Sun, Xu, Tang, Aihong, Tang, Zebo, Wang, Fuqiang, Wang, Hai, Wang, Yi, Xiao, Zhigang, Xie, Guannan, Xu, Nu, Xu, Qinghua, Xu, Zhangbu, Yang, Chi, Yang, Shuai, Zha, Wangmei, Zhang, Yapeng, Zhang, Yifei, Zhao, Jie, Zhu, Xianglei
In the paper, we discuss the development of the multi-gap resistive plate chamber Time-of-Flight (TOF) technology and the production of the STAR TOF detector in China at the beginning of the 21st century. Then we review recent experimental results fr
Externí odkaz:
http://arxiv.org/abs/2407.02935
Autor:
Ma, Yubo, Zang, Yuhang, Chen, Liangyu, Chen, Meiqi, Jiao, Yizhu, Li, Xinze, Lu, Xinyuan, Liu, Ziyu, Ma, Yan, Dong, Xiaoyi, Zhang, Pan, Pan, Liangming, Jiang, Yu-Gang, Wang, Jiaqi, Cao, Yixin, Sun, Aixin
Understanding documents with rich layouts and multi-modal components is a long-standing and practical task. Recent Large Vision-Language Models (LVLMs) have made remarkable strides in various tasks, particularly in single-page document understanding
Externí odkaz:
http://arxiv.org/abs/2407.01523
Image editing aims to edit the given synthetic or real image to meet the specific requirements from users. It is widely studied in recent years as a promising and challenging field of Artificial Intelligence Generative Content (AIGC). Recent signific
Externí odkaz:
http://arxiv.org/abs/2406.14555
As diffusion probabilistic models (DPMs) are being employed as mainstream models for generative artificial intelligence (AI), the study of their memorization of the raw training data has attracted growing attention. Existing works in this direction a
Externí odkaz:
http://arxiv.org/abs/2406.12752
Autor:
Wang, Jiaqi, Zang, Yuhang, Zhang, Pan, Chu, Tao, Cao, Yuhang, Sun, Zeyi, Liu, Ziyu, Dong, Xiaoyi, Wu, Tong, Lin, Dahua, Chen, Zeming, Wang, Zhi, Meng, Lingchen, Yao, Wenhao, Yang, Jianwei, Wu, Sihong, Chen, Zhineng, Wu, Zuxuan, Jiang, Yu-Gang, Wu, Peixi, Chai, Bosong, Nie, Xuan, Yan, Longquan, Wang, Zeyu, Zhou, Qifan, Wang, Boning, Huang, Jiaqi, Xu, Zunnan, Li, Xiu, Yuan, Kehong, Zu, Yanyan, Ha, Jiayao, Gao, Qiong, Jiao, Licheng
Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown or unseen objects. The challenges necessitate the development of publi
Externí odkaz:
http://arxiv.org/abs/2406.11739
This paper studies the problem of pre-training for small models, which is essential for many mobile devices. Current state-of-the-art methods on this problem transfer the representational knowledge of a large network (as a Teacher) into a smaller mod
Externí odkaz:
http://arxiv.org/abs/2406.11689
Autor:
Wu, Huang-Kai, Wang, Xi-Yang, Wang, Yu-Miao, Wang, You-Jing, Fang, De-Qing, He, Wan-Bing, Ma, Wei-Hu, Cao, Xi-Guang, Fu, Chang-Bo, Deng, Xian-Gai, Ma, Yu-Gang
Active Target Time Projection Chambers (AT-TPCs) are state-of-the-art tools in the field of low-energy nuclear physics, particularly suitable for experiments using low-intensity radioactive ion beams or gamma rays. The Fudan Multi-purpose Active Targ
Externí odkaz:
http://arxiv.org/abs/2406.18599
Autor:
Chen, Yiwen, He, Tong, Huang, Di, Ye, Weicai, Chen, Sijin, Tang, Jiaxiang, Chen, Xin, Cai, Zhongang, Yang, Lei, Yu, Gang, Lin, Guosheng, Zhang, Chi
Recently, 3D assets created via reconstruction and generation have matched the quality of manually crafted assets, highlighting their potential for replacement. However, this potential is largely unrealized because these assets always need to be conv
Externí odkaz:
http://arxiv.org/abs/2406.10163