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pro vyhledávání: '"Fang, Xi"'
Autor:
Liu, Xiaohong, Min, Xiongkuo, Zhai, Guangtao, Li, Chunyi, Kou, Tengchuan, Sun, Wei, Wu, Haoning, Gao, Yixuan, Cao, Yuqin, Zhang, Zicheng, Wu, Xiele, Timofte, Radu, Peng, Fei, Fu, Huiyuan, Ming, Anlong, Wang, Chuanming, Ma, Huadong, He, Shuai, Dou, Zifei, Chen, Shu, Zhang, Huacong, Xie, Haiyi, Wang, Chengwei, Chen, Baoying, Zeng, Jishen, Yang, Jianquan, Wang, Weigang, Fang, Xi, Lv, Xiaoxin, Yan, Jun, Zhi, Tianwu, Zhang, Yabin, Li, Yaohui, Li, Yang, Xu, Jingwen, Liu, Jianzhao, Liao, Yiting, Li, Junlin, Yu, Zihao, Lu, Yiting, Li, Xin, Motamednia, Hossein, Hosseini-Benvidi, S. Farhad, Guan, Fengbin, Mahmoudi-Aznaveh, Ahmad, Mansouri, Azadeh, Gankhuyag, Ganzorig, Yoon, Kihwan, Xu, Yifang, Fan, Haotian, Kong, Fangyuan, Zhao, Shiling, Dong, Weifeng, Yin, Haibing, Zhu, Li, Wang, Zhiling, Huang, Bingchen, Saha, Avinab, Mishra, Sandeep, Gupta, Shashank, Sureddi, Rajesh, Saha, Oindrila, Celona, Luigi, Bianco, Simone, Napoletano, Paolo, Schettini, Raimondo, Yang, Junfeng, Fu, Jing, Zhang, Wei, Cao, Wenzhi, Liu, Limei, Peng, Han, Yuan, Weijun, Li, Zhan, Cheng, Yihang, Deng, Yifan, Li, Haohui, Qu, Bowen, Li, Yao, Luo, Shuqing, Wang, Shunzhou, Gao, Wei, Lu, Zihao, Conde, Marcos V., Wang, Xinrui, Chen, Zhibo, Liao, Ruling, Ye, Yan, Wang, Qiulin, Li, Bing, Zhou, Zhaokun, Geng, Miao, Chen, Rui, Tao, Xin, Liang, Xiaoyu, Sun, Shangkun, Ma, Xingyuan, Li, Jiaze, Yang, Mengduo, Xu, Haoran, Zhou, Jie, Zhu, Shiding, Yu, Bohan, Chen, Pengfei, Xu, Xinrui, Shen, Jiabin, Duan, Zhichao, Asadi, Erfan, Liu, Jiahe, Yan, Qi, Qu, Youran, Zeng, Xiaohui, Wang, Lele, Liao, Renjie
This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2024. This challenge is to address a major
Externí odkaz:
http://arxiv.org/abs/2404.16687
The development of Large Language Models (LLM) and Diffusion Models brings the boom of Artificial Intelligence Generated Content (AIGC). It is essential to build an effective quality assessment framework to provide a quantifiable evaluation of differ
Externí odkaz:
http://arxiv.org/abs/2404.13299
Autor:
Fang, Xi, Xu, Weijie, Tan, Fiona Anting, Zhang, Jiani, Hu, Ziqing, Qi, Yanjun, Nickleach, Scott, Socolinsky, Diego, Sengamedu, Srinivasan, Faloutsos, Christos
Publikováno v:
TMLR 2024
Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table understanding. Eac
Externí odkaz:
http://arxiv.org/abs/2402.17944
Autor:
Qiao, Liang, Shi, Jun, Hao, Xiaoyu, Fang, Xi, Zhao, Minfan, Zhu, Ziqi, Chen, Junshi, An, Hong, Li, Bing, Yuan, Honghui, Wang, Xinyang, Tang, Xulong
Tensor program tuning is essential for the efficient deployment of deep neural networks. Search-based approaches have demonstrated scalability and effectiveness in automatically finding high-performance programs for specific hardware. However, the se
Externí odkaz:
http://arxiv.org/abs/2402.02361
Autor:
Xu, Weijie, Huang, Zicheng, Hu, Wenxiang, Fang, Xi, Cherukuri, Rajesh Kumar, Nayyar, Naumaan, Malandri, Lorenzo, Sengamedu, Srinivasan H.
Publikováno v:
EACL 2024
Recent advancements in Large Language Models (LLMs) have been reshaping Natural Language Processing (NLP) task in several domains. Their use in the field of Human Resources (HR) has still room for expansions and could be beneficial for several time c
Externí odkaz:
http://arxiv.org/abs/2402.01018
Defect inspection is paramount within the closed-loop manufacturing system. However, existing datasets for defect inspection often lack precision and semantic granularity required for practical applications. In this paper, we introduce the Defect Spe
Externí odkaz:
http://arxiv.org/abs/2310.17316
Autor:
Fang, Xi, Kim, Daeseung, Xu, Xuanang, Kuang, Tianshu, Lampen, Nathan, Lee, Jungwook, Deng, Hannah H., Gateno, Jaime, Liebschner, Michael A. K., Xia, James J., Yan, Pingkun
In CMF surgery, the planning of bony movement to achieve a desired facial outcome is a challenging task. Current bone driven approaches focus on normalizing the bone with the expectation that the facial appearance will be corrected accordingly. Howev
Externí odkaz:
http://arxiv.org/abs/2307.10954
Publikováno v:
European Journal of Medical Research, Vol 29, Iss 1, Pp 1-12 (2024)
Abstract Background Limited evidence exists regarding the link between platelet count and 30-day in-hospital mortality in acute respiratory failure (ARF) patients. Thus, this study aims to investigate this association among ICU patients experiencing
Externí odkaz:
https://doaj.org/article/a5eea12cab57487092d042dd072cb17b
Publikováno v:
Shiyan dongwu yu bijiao yixue, Vol 44, Iss 1, Pp 52-61 (2024)
ObjectiveTo explore the metabolic changes during the development of Tupaia belangeri breast tumors, to investigate the close relationship between the changes of serum metabolic substances and the occurrence and progression of tumors, and to screen fo
Externí odkaz:
https://doaj.org/article/08975f96cd3f4ca58a8e8bfe50d21a8c
The information bottleneck (IB) method is a feasible defense solution against adversarial attacks in deep learning. However, this method suffers from the spurious correlation, which leads to the limitation of its further improvement of adversarial ro
Externí odkaz:
http://arxiv.org/abs/2210.14229