Results 41 to 50 of about 2,466 (175)

Tibetan Few‐Shot Learning Model With Deep Contextualised Two‐Level Word Embeddings

CAAI Transactions on Intelligence Technology, Volume 10, Issue 5, Page 1394-1410, October 2025.
ABSTRACT Few‐shot learning is the task of identifying new text categories from a limited set of training examples. The two key challenges in few‐shot learning are insufficient understanding of new samples and imperfect modelling. The uniqueness of low‐resource languages lies in their limited linguistic resources, which directly leads to the difficulty ...
Ziyue Zhang, Yongbin Yu, Xiangxiang Wang, Xiao Feng, Yuze Li, Jiarun Shen, Dorje Tashi, Jin Zhang, Lobsang Yeshi, Lei Li, Nyima Tashi, Jingye Cai   +11 more
wiley   +1 more source

Assessment of the three representative empirical models for zenith tropospheric delay (ZTD) using the CMONOC data

Geodesy and Geodynamics
The precise correction of atmospheric zenith tropospheric delay (ZTD) is significant for the Global Navigation Satellite System (GNSS) performance regarding positioning accuracy and convergence time.
Debao Yuan, Jian Li, Yifan Yao, Fei Yang, Yingying Wang, Ran Chen, Tairan Xu   +6 more
doaj   +1 more source

Italian Crossword Generator: Enhancing Education through Interactive Word Puzzles

, 2023
Educational crosswords offer numerous benefits for students, including increased engagement, improved understanding, critical thinking, and memory retention.
Angelini, Giovanni, Gori, Marco, laquinta, Tommaso, Maggini, Marco, Rigutini, Leonardo, Zanollo, Asya, Zeinalipour, Kamyar   +6 more
core  

The Rise of Large Language Models: Evolution, Applications, and Future Directions

Engineering Reports, Volume 7, Issue 9, September 2025.
This paper provides a comprehensive Systematic Literature Review (SLR) on Large Language Models (LLMs), covering their evolution, applications, evaluation metrics, and challenges. It identifies key research gaps and future directions, offering a structured taxonomy and analysis of performance environments, datasets, and open issues in LLM research ...
Amir Masoud Rahmani, Atefeh Hemmati, Shirin Abbasi   +2 more
wiley   +1 more source

Does Writing with Language Models Reduce Content Diversity?

, 2023
Large language models (LLMs) have led to a surge in collaborative writing with model assistance. As different users incorporate suggestions from the same model, there is a risk of decreased diversity in the produced content, potentially limiting diverse ...
He, He, Padmakumar, Vishakh
core  

ML@ChemE: Past, Present, and Future of Machine Learning in Chemical Engineering

ChemBioEng Reviews, Volume 12, Issue 4, August 2025.
Although the initial machine learning (ML) applications were mainly on fault detection, signal processing, and process modeling, they extended to new areas like property estimation and material screening in later years; energy technologies, environmental issues, health, and new materials will likely be more important in future with the use of larger ...
Pınar Özdemir, Ramazan Yıldırım
wiley   +1 more source

SHAtropE—A Regional Gridded ZTD Model for China and the Surrounding Areas

Remote Sensing, 2020
A regional zenith tropospheric delay (ZTD) empirical model, referred to as SHAtropE (SHanghai Astronomical observatory tropospheric delay model—Extended), is developed and provides tropospheric propagation delay corrections for users in China and ...
Junping Chen, Jungang Wang, Ahao Wang, Junsheng Ding, Yize Zhang   +4 more
doaj   +1 more source

Optimizing PPP Performance by Incorporating ZWD Constraints Derived From Data Assimilation

Earth and Space Science, Volume 12, Issue 8, August 2025.
Abstract One of the primary error sources limiting the performance of the Precise Point Positioning (PPP) technique is the atmospheric wet delay, caused by the presence of water vapor in the lower atmosphere. Accurately representing this parameter is crucial for improving the initialization and accuracy of satellite‐based positioning techniques ...
Masoud Dehvari, Saeed Farzaneh, Ehsan Forootan   +2 more
wiley   +1 more source

Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

, 2023
Prompting-based large language models (LLMs) are surprisingly powerful at generating natural language reasoning steps or Chains-of-Thoughts (CoT) for multi-step question answering (QA).
Balasubramanian, Niranjan, Khot, Tushar, Sabharwal, Ashish, Trivedi, Harsh   +3 more
core  

CYGENT: A cybersecurity conversational agent with log summarization powered by GPT-3 [PDF]

In response to the escalating cyber-attacks in the modern IT and IoT landscape, we developed CYGENT, a conversational agent framework powered by GPT-3.5 turbo model, designed to aid system administrators in ensuring optimal performance and uninterrupted ...
Balasubramanian, Prasasthy, Kostakos, Panos, Seby, Justin   +2 more
core   +3 more sources