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pro vyhledávání: '"Wang, Tongnian"'
Federated learning (FL) enables edge devices to collaboratively train a machine learning model without sharing their raw data. Due to its privacy-protecting benefits, FL has been deployed in many real-world applications. However, deploying FL over mo
Externí odkaz:
http://arxiv.org/abs/2410.10833
Radiology report summarization (RRS) is crucial for patient care, requiring concise "Impressions" from detailed "Findings." This paper introduces a novel prompting strategy to enhance RRS by first generating a layperson summary. This approach normali
Externí odkaz:
http://arxiv.org/abs/2406.14500
Language models have seen significant growth in the size of their corpus, leading to notable performance improvements. Yet, there has been limited progress in developing models that handle smaller, more human-like datasets. As part of the BabyLM shar
Externí odkaz:
http://arxiv.org/abs/2310.16681
Autor:
Wang, Tongnian, Zhang, Kai, Cai, Jiannan, Gong, Yanmin, Choo, Kim-Kwang Raymond, Guo, Yuanxiong
Publikováno v:
Journal of Healthcare Informatics Research; Jun2024, Vol. 8 Issue 2, p181-205, 25p
Akademický článek
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Publikováno v:
In International Journal of Refractory Metals and Hard Materials March 2014 43:302-308
Publikováno v:
In Journal of Nuclear Materials November 2013 442(1-3) Supplement 1:S233-S236