Zobrazeno 1 - 10
of 1 099
pro vyhledávání: '"Huang Xiaolong"'
Autor:
Feng Guo, Huang Xiaolong, Jiang Feng, Yang Qing, Jin Wenwei, Shao Chuan, Liu Jianmin, Dahai Wang, Jian Liang
Publikováno v:
Processing and Application of Ceramics, Vol 18, Iss 1, Pp 109-116 (2024)
Novel tungstate SrLa6-xW10O40: xEu3+ (x = 0, 0.03, 0.06, 0.09, 0.12, 0.15, 0.18, 0.21) red phosphors were prepared by solid state method at 1150 °C by using SrCO3, La2O3, WO3 and Eu2O3 as raw materials. The powders were agglomerated with particles h
Externí odkaz:
https://doaj.org/article/1bf197912d4c4a0cabcd08ec36f10671
Publikováno v:
Dizhi lixue xuebao, Vol 27, Iss 6, Pp 913-927 (2021)
The Midu area is located at the southeast end of the northwestern Yunnan fault depression zone, the intersection of the Red River fault zone and the Chenghai fault. It is a key area for uncovering the formation mechanism of the Northwest Yunnan fault
Externí odkaz:
https://doaj.org/article/3d507059e7114106868d372eb04c3d6f
Autor:
WANG Guangming, WU Zhonghai, PENG Guanling, LIU Zifeng, LUO Ruijie, HUANG Xiaolong, CHEN Haopeng
Publikováno v:
Dizhi lixue xuebao, Vol 27, Iss 4, Pp 662-678 (2021)
According to China Earthquake Network Center (CENC), the MS 6.4 Yangbi earthquake struck northwestern Yunnan Province on 21 May, 2021 at 21:48(Beijing time). Figuring out the seismogenic fault and source rupture characteristics in time can provide a
Externí odkaz:
https://doaj.org/article/6e5ba58b3768481bb9d98a9b851aeeb9
Autor:
Liu, Mugeng, Huang, Xiaolong, He, Wei, Xie, Yibing, Zhang, Jie M., Jing, Xiang, Chen, Zhenpeng, Ma, Yun
The Software Engineering (SE) community has been embracing the open science policy and encouraging researchers to disclose artifacts in their publications. However, the status and trends of artifact practice and quality remain unclear, lacking insigh
Externí odkaz:
http://arxiv.org/abs/2404.06852
Autor:
Li, Haoran, Dong, Qingxiu, Tang, Zhengyang, Wang, Chaojun, Zhang, Xingxing, Huang, Haoyang, Huang, Shaohan, Huang, Xiaolong, Huang, Zeqiang, Zhang, Dongdong, Gu, Yuxian, Cheng, Xin, Wang, Xun, Chen, Si-Qing, Dong, Li, Lu, Wei, Sui, Zhifang, Wang, Benyou, Lam, Wai, Wei, Furu
We introduce Generalized Instruction Tuning (called GLAN), a general and scalable method for instruction tuning of Large Language Models (LLMs). Unlike prior work that relies on seed examples or existing datasets to construct instruction tuning data,
Externí odkaz:
http://arxiv.org/abs/2402.13064
This technical report presents the training methodology and evaluation results of the open-source multilingual E5 text embedding models, released in mid-2023. Three embedding models of different sizes (small / base / large) are provided, offering a b
Externí odkaz:
http://arxiv.org/abs/2402.05672
Visual fine-tuning has garnered significant attention with the rise of pre-trained vision models. The current prevailing method, full fine-tuning, suffers from the issue of knowledge forgetting as it focuses solely on fitting the downstream training
Externí odkaz:
http://arxiv.org/abs/2401.10962
In this paper, we introduce a novel and simple method for obtaining high-quality text embeddings using only synthetic data and less than 1k training steps. Unlike existing methods that often depend on multi-stage intermediate pre-training with billio
Externí odkaz:
http://arxiv.org/abs/2401.00368
Modern search engines are built on a stack of different components, including query understanding, retrieval, multi-stage ranking, and question answering, among others. These components are often optimized and deployed independently. In this paper, w
Externí odkaz:
http://arxiv.org/abs/2310.14587
Publikováno v:
Knowledge and Management of Aquatic Ecosystems, Vol 0, Iss 422, p 11 (2021)
The submerged species Carolina fanwort (Cabomba caroliniana) has attracted considerable attention in Lake Taihu Basin (LTB), China. This species was widely used as a garden plant until 2016, when it was identified as invasive. In this study, we condu
Externí odkaz:
https://doaj.org/article/6259f548e07e46bf8c1ea8f56fdcf077