Zobrazeno 1 - 10
of 123
pro vyhledávání: '"Li‐Feng Lin"'
Autor:
Xue-yan Zheng, Shu-jun Guo, Jian-xiong Hu, Rui-lin Meng, Yan-jun Xu, Yun-hong Lv, Ye Wang, Ni Xiao, Chuan Li, Xiao-jun Xu, De-jian Zhao, Hong-ye Zhou, Jia-hui He, Xiao-min Tan, Jing Wei, Li-feng Lin, Wei-jie Guan
Publikováno v:
ERJ Open Research, Vol 10, Iss 4 (2024)
Background Few studies have compared the associations between long-term exposures to particulate matters (aerodynamic diameter ≤1, ≤2.5 and ≤10 µm: PM1, PM2.5 and PM10, respectively) and asthma and asthma-related respiratory symptoms. The obje
Externí odkaz:
https://doaj.org/article/d4ca01abc0bb41d59d753638040c1580
Autor:
Xue-yan Zheng, Si-li Tang, Tao Liu, Ye Wang, Xiao-jun Xu, Ni Xiao, Chuan Li, Yan-jun Xu, Zhao-xuan He, Shu-li Ma, Yu-liang Chen, Rui-lin Meng, Li-feng Lin
Publikováno v:
Environmental Health, Vol 21, Iss 1, Pp 1-11 (2022)
Abstract Background We aimed to explore the association between long-term exposure to particulate matter ≤ 2.5 µm (PM2.5) and metabolic syndrome (MetS) and its components including fasting blood glucose (FBG), blood pressure, triglyceride (TG), hi
Externí odkaz:
https://doaj.org/article/b2cad73d483148e2aef35f6a10eaa55a
Direct Preference Optimization (DPO) has emerged as a more computationally efficient alternative to Reinforcement Learning from Human Feedback (RLHF) with Proximal Policy Optimization (PPO), eliminating the need for reward models and online sampling.
Externí odkaz:
http://arxiv.org/abs/2410.04834
Autor:
Chuan Li, Xue-yan Zheng, Xiao-jun Xu, Li-feng Lin, Xia-zi Lin, Rui-lin Meng, Dan-dan Peng, Hao-feng Xu
Publikováno v:
BMJ Open, Vol 12, Iss 11 (2022)
Objective This study aims to investigate the prevalence and risk factors of falls among the elderly in Guangdong, China.Methods A cross-sectional study was conducted in six communities of Guangdong province. People over 60 years old were selected wit
Externí odkaz:
https://doaj.org/article/8800582bd2f343dd8e85da79b953d80e
Autor:
Xue-yan Zheng, Xiao-jun Xu, Yi-yang Liu, Yan-jun Xu, Si-xing Pan, Xin-ying Zeng, Qian Yi, Ni Xiao, Li-feng Lin
Publikováno v:
BMC Public Health, Vol 20, Iss 1, Pp 1-20 (2020)
Abstract Background Guangdong province is dominated by three cultural regions: Canton, Hakka and Hoklo. However, little is known about the disease burden within these regions, particularly because different population,environmental and socioeconomic
Externí odkaz:
https://doaj.org/article/d8bd714afa154583a360fc066bedd363
Autor:
Li-Feng Lin
Publikováno v:
Tourism and Hospitality Management, Vol 25, Iss 2, Pp 291-310 (2019)
Purpose – The present study analyzes how economic factors and online searching behavior influence the demand for international tourism and how to improve the relevance and prognostics between the active searching behavior and the tourism industry.
Externí odkaz:
https://doaj.org/article/acc3266c83434f969a5cfcc6478a11a1
Autor:
Xue-yan Zheng, Yan-jun Xu, Shu-li Ma, Si-li Tang, Li-feng Lin, Wei-Jie Guan, Xiaojun Xu, Haofeng Xu, Ying-Shan Xu
Publikováno v:
BMJ Open, Vol 11, Iss 6 (2021)
Objective We aimed to ascertain the trends of injury mortality during the COVID-19 period in southern China.Methods We conducted a population-based retrospective analysis to compare the mortality changes of all-cause injury and transport injuries, po
Externí odkaz:
https://doaj.org/article/8e6d0c241c024a6b807173127f2041b2
While Reinforcement Learning from Human Feedback (RLHF) significantly enhances the generation quality of Large Language Models (LLMs), recent studies have raised concerns regarding the complexity and instability associated with the Proximal Policy Op
Externí odkaz:
http://arxiv.org/abs/2402.16030
Knowledge distillation is of key importance to launching multilingual pre-trained language models for real applications. To support cost-effective language inference in multilingual settings, we propose AMTSS, an adaptive multi-teacher single-student
Externí odkaz:
http://arxiv.org/abs/2305.07928
Although pre-trained language models (PLMs) have achieved state-of-the-art performance on various natural language processing (NLP) tasks, they are shown to be lacking in knowledge when dealing with knowledge driven tasks. Despite the many efforts ma
Externí odkaz:
http://arxiv.org/abs/2208.00635