Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
Large Language Models (LLMs) have recently gathered attention with the release of ChatGPT, a user-centered chatbot released by OpenAI. Infodemic is a trending topic in public health and the ability of...
Abstract This systematic review provides unique findings with an up-to-date examination of artificial intelligence (AI) in higher education (HE) from 2016 to 2022. Five usage codes emerged from the da...
Pre-trained large language models (“LLMs”) like GPT-3 can engage in fluent, multi-turn instruction-taking out-of-the-box, making them attractive materials for designing natural language interactions....
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated applications, but the outcomes of many AI models are challenging to comprehend and trust due to their black-bo...
Abstract Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can be applied across various sectors. Pertinently, hybrid conventional DL architectures have the capacity...
Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal fie...
The recent breakthroughs in natural language processing for model pretraining on large quantities of data have opened the way for similar foundation models in computer vision. In terms of data, we pro...
Abstract Data scarcity is a major challenge when training deep learning (DL) models. The survey ends with a list of applications that suffer from data scarcity, several alternatives are proposed in or...
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine. We expect that GMAI-enabled applications w...
This research explores Transformers in medical imaging: A survey, contributing new insights to the field of Artificial Intelligence.
In this technology review, we explore the affordances of the generative AI chatbot ChatGPT for language teaching and learning. In addition to this, we also present debates and drawbacks of ChatGPT.
Artificial intelligence (AI) introduces new tools to the educational environment with the potential to transform conventional teaching and learning processes. In addition to the advantages of cutting-...
We study the staggered introduction of a generative AI-based conversational assistant using data from 5,179 customer support agents.Access to the tool increases productivity, as measured by issues res...
This first article in a series describes the history of artificial intelligence in medicine; the use of AI in image analysis, identification of disease outbreaks, and diagnosis; and the use of chatbot...
Denoising diffusion models represent a recent emerging topic in computer vision, demonstrating remarkable results in the area of generative modeling. Then, we introduce a multi-perspective categorizat...
Abstract This review discussed the dilemma of small data faced by materials machine learning. Next, the methods of dealing with small data were introduced, including data extraction from publications,...
Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our unde...
Abstract The advent of generative artificial intelligence (AI) offers transformative potential in the field of education. ChatGPT was used as a research tool for assistance with editing and to experim...
This perspective article on using partial least squares structural equation modelling (PLS-SEM) is intended as a guide for authors who wish to publish datasets that can be analysed with this method as...
The release of ChatGPT has sparked significant academic integrity concerns in higher education. Similarly, the students’ voice is poorly represented in media articles to date.