Results 61 to 70 of about 428 (156)

Scaling Laws for Discriminative Classification in Large Language Models

Applied AI Letters, Volume 6, Issue 1, February 2025.
ABSTRACT Modern large language models (LLMs) represent a paradigm shift in what can plausibly be expected of machine learning models. The fact that LLMs can effectively generate sensible answers to a diverse range of queries suggests that they would be useful in customer support applications.
Dean Wyatte, Fatemeh Tahmasbi, Ming Li, Thomas Markovich   +3 more
wiley   +1 more source

You're (Not) My Type‐ Can LLMs Generate Feedback of Specific Types for Introductory Programming Tasks?

Journal of Computer Assisted Learning, Volume 41, Issue 1, February 2025.
ABSTRACT Background Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience.
Dominic Lohr, Hieke Keuning, Natalie Kiesler   +2 more
wiley   +1 more source

Deep Neural Networks for Refining Vertical Modeling of Global Tropospheric Delay

Geophysical Research Letters, Volume 52, Issue 2, 28 January 2025.
Abstract Kinematic airborne platforms are becoming increasingly vital for Earth observation. They highlight the critical need for accurate tropospheric delay corrections across varying altitudes, especially as most existing models are limited to Earth's surface.
Peng Yuan, Kyriakos Balidakis, Jungang Wang, Pengfei Xia, Jian Wang, Mingyuan Zhang, Weiping Jiang, Harald Schuh, Jens Wickert, Zhiguo Deng   +9 more
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

How the technologies behind self‐driving cars, social networks, ChatGPT, and DALL‐E2 are changing structural biology

BioEssays, Volume 47, Issue 1, January 2025.
Deep learning, a brain inspired field of computer science, revolutionizes structural biology. I summarize how convolutional neural networks (CNNs), large language models (LLMs), denoising diffusion probabilistic models (DDPMs)/Noise conditional score networks (NCSNs), and graph neural networks (GNNs) have impacted protein structure prediction, inverse ...
Matthias Bochtler
wiley   +1 more source

Utilizing large language models for EFL essay grading: An examination of reliability and validity in rubric‐based assessments

British Journal of Educational Technology, Volume 56, Issue 1, Page 150-166, January 2025.
Abstract This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student
Fatih Yavuz, Özgür Çelik, Gamze Yavaş Çelik   +2 more
wiley   +1 more source

"Künstliche Intelligenz" à la GPT3: Die große Remix-Maschine

, 2023
GPT3 ist eine Software, mit der sich wie von Zauberhand Texte erstellen lassen. Das Etikett "Künstliche Intelligenz" dürfte trotz aller Hoffnungen zu hoch gegriffen sein. Denn GPT3 erzeugt vor allem Remixes von bestehenden Texten. Wie lernt die Maschine zu schreiben? Und ist die neue Technologie Fluch oder Segen für die Kreativbranche?
openaire   +1 more source

Privacy preserving large language models: ChatGPT case study based vision and framework

IET Blockchain, Volume 4, Issue S1, Page 706-724, December 2024.
We propose the conceptual model called PrivChatGPT, a privacy‐preserving model for LLMs that consists of two main components, that is, preserving user privacy during the data curation/pre‐processing together with preserving private context and the private training process for large‐scale data.
Imdad Ullah, Najm Hassan, Sukhpal Singh Gill, Basem Suleiman, Tariq Ahamed Ahanger, Zawar Shah, Junaid Qadir, Salil S. Kanhere   +7 more
wiley   +1 more source

Quantitative analysis of the tropospheric delay difference using empirical mapping functions on VLBI stations

Frontiers in Astronomy and Space Sciences
Tropospheric delay is a major error source for the high-accuracy Very Long Baseline Interferometry (VLBI) technique due to rapid water vapor variations. The Niell mapping function (NMF) and Global Mapping Function (GMF) are extensively applied to convert
W. L. Zhou, W. L. Zhou, W. L. Zhou, W. L. Zhou, S. L. Song, S. L. Song, J. Jiang, J. Jiang, X. Hu, P. J. Li, P. J. Li, Z. B. Zhang, Z. B. Zhang, Z. B. Zhang   +13 more
doaj   +1 more source

Comparative analysis of paraphrasing performance of ChatGPT, GPT‐3, and T5 language models using a new ChatGPT generated dataset: ParaGPT

Expert Systems, Volume 41, Issue 11, November 2024.
Abstract Paraphrase generation is a fundamental natural language processing (NLP) task that refers to the process of generating a well‐formed and coherent output sentence that exhibits both syntactic and/or lexical diversity from the input sentence, while simultaneously ensuring that the semantic similarity between the two sentences is preserved ...
Meltem Kurt Pehlivanoğlu, Robera Tadesse Gobosho, Muhammad Abdan Syakura, Vimal Shanmuganathan, Luis de‐la‐Fuente‐Valentín   +4 more
wiley   +1 more source