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pro vyhledávání: '"LIU, YIZHI"'
Large Language Models (LLMs), while being increasingly dominant on a myriad of knowledge-intensive activities, have only had limited success understanding lengthy table-text mixtures, such as academic papers and financial reports. Recent advances of
Externí odkaz:
http://arxiv.org/abs/2412.09884
Autor:
Zheng, Yingfeng, Wang, Wei, Zhong, Yuxin, Wu, Fengchun, Zhu, Zhuoting, Tham, Yih-Chung, Lamoureux, Ecosse, Xiao, Liang, Zhu, Erta, Liu, Haoning, Jin, Ling, Liang, Linyi, Luo, Lixia, He, Mingguang, Morgan, Ian, Congdon, Nathan, Liu, Yizhi
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 4, p e24316 (2021)
BackgroundThe COVID-19 pandemic has led to worldwide school closures, with millions of children confined to online learning at home. As a result, children may be susceptible to anxiety and digital eye strain, highlighting a need for population interv
Externí odkaz:
https://doaj.org/article/fe63d26caac943a7a7d7c3f4d755ee85
Electronic health records (EHRs) serve as an essential data source for the envisioned artificial intelligence (AI)-driven transformation in healthcare. However, clinician biases reflected in EHR notes can lead to AI models inheriting and amplifying t
Externí odkaz:
http://arxiv.org/abs/2305.10201
Autor:
Yu, Cody Hao, Fan, Haozheng, Huang, Guangtai, Jia, Zhen, Liu, Yizhi, Wang, Jie, Zheng, Zach, Zhou, Yuan, Shen, Haichen, Shao, Junru, Li, Mu, Wang, Yida
As deep learning is pervasive in modern applications, many deep learning frameworks are presented for deep learning practitioners to develop and train DNN models rapidly. Meanwhile, as training large deep learning models becomes a trend in recent yea
Externí odkaz:
http://arxiv.org/abs/2303.04759
Publikováno v:
ASPLOS 2023: Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2, January 2023, Pages 370-384
As deep learning models nowadays are widely adopted by both cloud services and edge devices, reducing the latency of deep learning model inferences becomes crucial to provide efficient model serving. However, it is challenging to develop efficient te
Externí odkaz:
http://arxiv.org/abs/2210.09603
Publikováno v:
The Electronic Library, 2023, Vol. 42, Issue 1, pp. 37-59.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EL-06-2023-0143
Autor:
Yang, Jiayi, Wang, Zidong, Jiang, Jing, Tian, Huiling, Wang, Shun, Liu, Yizhi, Cao, Zumao, Yang, Changqing Joseph, Li, Zhigang
Publikováno v:
In Journal of Traditional Chinese Medical Sciences October 2024 11(4):500-512
Publikováno v:
In Automation in Construction October 2024 166
Internet users have been exposing an increasing amount of Personally Identifiable Information (PII) on social media. Such exposed PII can cause severe losses to the users, and informing users of their PII exposure is crucial to raise their privacy aw
Externí odkaz:
http://arxiv.org/abs/2111.09415
Autor:
Tang, Zequn, Zhao, Yilin, Wang, Zishuai, Liu, Xianrui, Liu, Yizhi, Gu, Penghao, Xiao, Gang, Baeyens, Jan, Su, Haijia
Publikováno v:
In Chemical Engineering Journal 1 September 2024 495