Zobrazeno 1 - 10
of 236
pro vyhledávání: '"Ning Qiang"'
Publikováno v:
NeuroImage, Vol 287, Iss , Pp 120519- (2024)
Functional brain networks (FBNs) are spatial patterns of brain function that play a critical role in understanding human brain function. There are many proposed methods for mapping the spatial patterns of brain function, however they oversimplify the
Externí odkaz:
https://doaj.org/article/daa01fcdbbe74f75829e9cec99285573
Autor:
Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Lin Zhao, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, Bao Ge
Publikováno v:
Meta-Radiology, Vol 1, Iss 2, Pp 100017- (2023)
This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains. Indeed, key innovations such as l
Externí odkaz:
https://doaj.org/article/47fd0baa31f443258bb73cec5412bacc
Publikováno v:
Frontiers in Neuroscience, Vol 17 (2023)
The investigation of functional brain networks (FBNs) using task-based functional magnetic resonance imaging (tfMRI) has gained significant attention in the field of neuroimaging. Despite the availability of several methods for constructing FBNs, inc
Externí odkaz:
https://doaj.org/article/d11efe485767425593d2a1b1be739232
Publikováno v:
Separations, Vol 10, Iss 11, p 571 (2023)
In this study, the diffusion, separation, and buffering of volatile organic compounds emitted in a non-steady state on activated carbon were studied. Ethanol and xylene, which have large differences in adsorption capacity and diffusion rate, were sel
Externí odkaz:
https://doaj.org/article/1681fdb528d041ab98707d37af7cdb56
Autor:
Zhenyuan, Yang, Zhengliang, Liu, Jing, Zhang, Cen, Lu, Jiaxin, Tai, Tianyang, Zhong, Yiwei, Li, Siyan, Zhao, Teng, Yao, Qing, Liu, Jinlin, Yang, Qixin, Liu, Zhaowei, Li, Kexin, Wang, Longjun, Ma, Dajiang, Zhu, Yudan, Ren, Bao, Ge, Wei, Zhang, Ning, Qiang, Tuo, Zhang, Tianming, Liu
This study examines the capabilities of advanced Large Language Models (LLMs), particularly the o1 model, in the context of literary analysis. The outputs of these models are compared directly to those produced by graduate-level human participants. B
Externí odkaz:
http://arxiv.org/abs/2410.18142
Autor:
Liu, Siyi, Ning, Qiang, Halder, Kishaloy, Xiao, Wei, Qi, Zheng, Htut, Phu Mon, Zhang, Yi, John, Neha Anna, Min, Bonan, Benajiba, Yassine, Roth, Dan
Open domain question answering systems frequently rely on information retrieved from large collections of text (such as the Web) to answer questions. However, such collections of text often contain conflicting information, and indiscriminately depend
Externí odkaz:
http://arxiv.org/abs/2410.12311
Autor:
Tianzhe Shi, Ning Qiang, Tao Liu, Jiao He, Haichao Miao, Zhaohai Li, Yiqi Cao, Shumin Chen, Xianbin Shi
Publikováno v:
Separations, Vol 10, Iss 3, p 213 (2023)
In this paper, the mechanism of separation of volatile organic compounds (VOCs) from activated carbon adsorption beds during closed cycle temperature swing desorption was studied. Toluene gas at different concentrations was used as the gas for closed
Externí odkaz:
https://doaj.org/article/6b1e849b8f0a4bf598bc470a4876d137
Publikováno v:
IEEE Access, Vol 8, Pp 4838-4859 (2020)
One of most primitive problems by unmanned underwater vehicle intelligent swarm (UIS) is coordination control, which has a great significance for realization of target hunting with great performance of efficiency and robustness. Existing studies conc
Externí odkaz:
https://doaj.org/article/af1d67b234e6475394b52fa0ebadc011
Autor:
Wang, Fei, Shang, Chao, Jain, Sarthak, Wang, Shuai, Ning, Qiang, Min, Bonan, Castelli, Vittorio, Benajiba, Yassine, Roth, Dan
User alignment is crucial for adapting general-purpose language models (LMs) to downstream tasks, but human annotations are often not available for all types of instructions, especially those with customized constraints. We observe that user instruct
Externí odkaz:
http://arxiv.org/abs/2403.06326
Autor:
Liu, Dan1 (AUTHOR), Ning, Qiang1 (AUTHOR), Zhai, Lihong2 (AUTHOR), Teng, Feng3 (AUTHOR), Li, Yunfu1 (AUTHOR), Zhao, Ran1 (AUTHOR), Xiong, Qing1 (AUTHOR), Zhan, Jimin1 (AUTHOR), Li, Zhen1 (AUTHOR), Yang, Fang1 (AUTHOR), Zhang, Zuxin1,4 (AUTHOR) zuxinzhang@mail.hzau.edu.cn, Liu, Lei1 (AUTHOR) leil@mail.hzau.edu.cn
Publikováno v:
Plant Biotechnology Journal. Oct2024, Vol. 22 Issue 10, p2675-2687. 13p.