A brief overview of ChatGPT: The history, status quo and potential future development

T Wu, S He, J Liu, S Sun, K Liu… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
ChatGPT, an artificial intelligence generated content (AIGC) model developed by OpenAI,
has attracted world-wide attention for its capability of dealing with challenging language …

[HTML][HTML] Artificial intelligence: A powerful paradigm for scientific research

Y Xu, X Liu, X Cao, C Huang, E Liu, S Qian, X Liu… - The Innovation, 2021 - cell.com
Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well
known from computer science is broadly affecting many aspects of various fields including …

Unifying large language models and knowledge graphs: A roadmap

S Pan, L Luo, Y Wang, C Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …

[HTML][HTML] Knowledge graphs: Opportunities and challenges

C Peng, F Xia, M Naseriparsa, F Osborne - Artificial Intelligence Review, 2023 - Springer
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally
important to organize and represent the enormous volume of knowledge appropriately. As …

Graph self-supervised learning: A survey

Y Liu, M Jin, S Pan, C Zhou, Y Zheng… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Deep learning on graphs has attracted significant interests recently. However, most of the
works have focused on (semi-) supervised learning, resulting in shortcomings including …

Graph learning: A survey

F Xia, K Sun, S Yu, A Aziz, L Wan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Graphs are widely used as a popular representation of the network structure of connected
data. Graph data can be found in a broad spectrum of application domains such as social …

Graph neural networks for natural language processing: A survey

L Wu, Y Chen, K Shen, X Guo, H Gao… - … and Trends® in …, 2023 - nowpublishers.com
Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies

A Thelen, X Zhang, O Fink, Y Lu, S Ghosh… - Structural and …, 2022 - Springer
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …

Toward better drug discovery with knowledge graph

X Zeng, X Tu, Y Liu, X Fu, Y Su - Current opinion in structural biology, 2022 - Elsevier
Drug discovery is the process of new drug identification. This process is driven by the
increasing data from existing chemical libraries and data banks. The knowledge graph is …

Gpt4graph: Can large language models understand graph structured data? an empirical evaluation and benchmarking

J Guo, L Du, H Liu, M Zhou, X He, S Han - arXiv preprint arXiv:2305.15066, 2023 - arxiv.org
Large language models~(LLM) like ChatGPT have become indispensable to artificial
general intelligence~(AGI), demonstrating excellent performance in various natural …