Results 91 to 100 of about 2,779 (194)

GFZTD: A Multimodal Fusion-Driven 3-D Tropospheric Delay Prediction Model Coupling Self-Attention and ConvLSTM

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Tropospheric delay, for which water vapor is a major cause, is a significant source of error in the global navigation satellite system. This article presents the gray figure-based zenith tropospheric delay prediction (GFZTD) model, which is built on ...
Yixin Zhu, Zhimin Sha, Pengzhi Wei, Shirong Ye, Pengfei Xia, Fangxin Hu   +5 more
doaj   +1 more source

Higher accuracy estimation of the weighted mean temperature (tm) with the aid of machine learning and NWP model

All Earth
An accurate calculation of weighted mean temperature (Tm) is highly critical for global navigation satellite system (GNSS) based precipitable water vapour retrieval.
Mingyun Hu, Junyu Li, Chaolong Yao, Feijuan Li, Lilong Liu, Liangke Huang, Yuxin Wang   +6 more
doaj   +1 more source

Benchmarks for Pir\'a 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change

, 2023
Pir\'a is a reading comprehension dataset focused on the ocean, the Brazilian coast, and climate change, built from a collection of scientific abstracts and reports on these topics.
Brandão, Anarosa A. F., Costa, Anna H. R., Cozman, Fabio G., José, Marcos M., Nakasato, Flávio, Peres, Sarajane M., Pirozelli, Paulo, Silveira, Igor   +7 more
core  

Extending Feature-Based Detection for Artificial Intelligence [PDF]

AI text generation is rapidly developing, and, as a result, it is becoming increasingly difficult to differentiate it from human written text. Our base study by Leon Fröhling et al.
Ahrndt, Kayla
core   +1 more source

Empirical tropospheric zenith wet delay models with strong generalization capability based on a robust machine learning fusion algorithm

Geodesy and Geodynamics
Tropospheric zenith wet delay (ZWD) plays a vital role in the analysis of space geodetic observations. In recent years, machine learning methods have been increasingly applied to improve the accuracy of ZWD calculations.
Jiahao Zhang, Qin Liang, Yunqing Huang
doaj   +1 more source

Self-Edit: Fault-Aware Code Editor for Code Generation

, 2023
Large language models (LLMs) have demonstrated an impressive ability to generate codes on competitive programming tasks. However, with limited sample numbers, LLMs still suffer from poor accuracy.
Jin, Zhi, Li, Ge, Li, Jia, Li, Zhuo, Zhang, Kechi   +4 more
core  

Opinerium: Subjective Question Generation Using Large Language Models

IEEE Access
This paper presents a comprehensive study on generating subjective inquiries for news media posts to empower public engagement with trending media topics.
Pedram Babakhani, Andreas Lommatzsch, Torben Brodt, Doreen Sacker, Fikret Sivrikaya, Sahin Albayrak   +5 more
doaj   +1 more source

Large Language Models Still Can't Plan (A Benchmark for LLMs on Planning and Reasoning about Change)

, 2023
Recent advances in large language models (LLMs) have transformed the field of natural language processing (NLP). From GPT-3 to PaLM, the state-of-the-art performance on natural language tasks is being pushed forward with every new large language model ...
Kambhampati, Subbarao, Olmo, Alberto, Sreedharan, Sarath, Valmeekam, Karthik   +3 more
core  

Fake and Real Tweet Classification Using a Pre-Trained GPT-3 Approach [PDF]

Advances in Engineering and Intelligence Systems
The widespread utilization of social media has precipitated a notable upsurge in the dissemination of inaccurate information. This underscores the urgency to counteract the propagation of falsehoods and decrease the reliance on these platforms as sources
Delveen Luqman Abd Alnabi
doaj   +1 more source

Optimization and Construction of Jinan Regional Tm Model Based on LSTM and Analysis of Its Influence on the Accuracy of GNSS Inversion PWV

Atmosphere
Water vapor constitutes a vital component of atmospheric precipitation, serving as the fundamental material basis for weather phenomena such as rainfall, and is a significant factor contributing to extreme weather events.
Shukai Wang, Qiuying Guo, Guihong Hua, Yingjun Sun, Wengang Sang, Zhengyu Wang   +5 more
doaj   +1 more source