Results 131 to 140 of about 23,670,881 (172)

A precipitation forecast model with a neural network and improved GPT3 model for Japan

GPS Solutions, 2023
Song Li, Nan Jiang, Tianhe Xu, Yan Xu, Honglei Yang, Zhen Zhang, Ao Guo, Yuhao Wu   +7 more
openaire   +2 more sources

A refined zenith tropospheric delay model for Mainland China based on the global pressure and temperature 3 (GPT3) model and random forest

GPS Solutions, 2023
Junyu Li, Qinglan Zhang, Lilong Liu, Yibin Yao, Liangke Huang, Fade Chen, Lv Zhou, Bao Zhang   +7 more
openaire   +2 more sources

Higher accuracy estimation of the weighted mean temperature (Tm) using GPT3 model with new grid coefficients over China

Atmospheric Research
Fei Yang, Mingjia Liu, Yanlin Zhao, Xiangdong An, Lei Wang, Zhuoyue Wen   +5 more
openaire   +2 more sources

A regional area-precise ZTD forecasting model combining GPT3 and GNSS based on an ensemble learning algorithm

GPS Solutions
Shaoni Chen, Chunhua Jiang, Pan Li, Huizhong Zhu, Junhua Kang, Xiang Gao, Shuaimin Wang, Guangsheng Liu   +7 more
openaire   +2 more sources

Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model

North American Chapter of the Association for Computational Linguistics, 2023
We present Impossible Distillation, a novel framework for paraphrasing and sentence summarization, that distills a high-quality dataset and model from a low-quality teacher that itself cannot perform these tasks.
Jaehun Jung, Peter West, Liwei Jiang, Faeze Brahman, Ximing Lu, Jillian R. Fisher, Taylor Sorensen, Yejin Choi   +7 more
semanticscholar   +1 more source

PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation

Conference on Empirical Methods in Natural Language Processing, 2023
Data augmentation is a widely used technique to address the problem of text classification when there is a limited amount of training data. Recent work often tackles this problem using large language models (LLMs) like GPT3 that can generate new examples
Gaurav Sahu, Olga Vechtomova, Dzmitry Bahdanau, I. Laradji   +3 more
semanticscholar   +1 more source

Machine Learning‐Based Model for Real‐Time GNSS Precipitable Water Vapor Sensing

Geophysical Research Letters, 2022
Global Navigation Satellite Systems (GNSS) provide a promising opportunity for real‐time precipitable water vapor (PWV) sensing. However, relying on meteorological information restrains the implementation of real‐time inversion from tropospheric zenith ...
Yuxin Zheng, Cuixian Lu, Zhilu Wu, Jianchi Liao, Yushan Zhang, Qiuyi Wang   +5 more
semanticscholar   +1 more source

A new tropospheric delay combination prediction model based on time series decomposition and deep learning

Advances in Space Research
Zenith tropospheric delay (ZTD) prediction is of great signi cance for high-precision navigation. However, ZTD modeling has proved to be challenging due to the presence of linear and nonlinear characteristics.
Yingchun Yue, Yixuan Wang, Shangguan Ming, X. Xu, Yifan Liang, Shaofeng Bian, Guojun Zhai   +6 more
semanticscholar   +1 more source

Vertical correction model of ZTD in China region based on polynomial residual compensation

Fourth International Conference on Geoscience and Remote Sensing Mapping
In order to solve the problem that the existing zenith tropospheric delay (ZTD) models in China oftenuse the exponential function with low accuracy at low elevation for vertical correction and ignore the residuals of the fitting function, the ERA5 data ...
Zicheng Wang
semanticscholar   +1 more source