With the development of blockchain technology, smart contracts have beco...
Large Language Models (LLMs) have drawn widespread attention and researc...
With the increasing popularity of cryptocurrencies and blockchain techno...
Graph Neural Networks (GNNs) have achieved state-of-the-art performance ...
To solve the inherent incompleteness of knowledge graphs (KGs), numbers ...
Knowledge graph completion (KGC) aims to solve the incompleteness of
kno...
Graph Neural networks (GNNs) have been applied in many scenarios due to ...
Oversmoothing is a common phenomenon in graph neural networks (GNNs), in...
Artificial Intelligence Generated Content (AIGC) is one of the latest
ac...
While contrastive self-supervised learning has become the de-facto learn...
The rapid development of digital economy has led to the emergence of var...
Recently, the birth of non-fungible tokens (NFTs) has attracted great
at...
With the overall momentum of the blockchain industry, crypto-based crime...
The prevalence of large-scale graphs poses great challenges in time and
...
The Smart Contract Weakness Classification Registry (SWC Registry) is a
...
A key constraint that limits the implementation of blockchain in Interne...
Web3, the next generation of the Internet, represents a decentralized an...
Graph contrastive learning defines a contrastive task to pull similar
in...
Metaverse, the core of the next-generation Internet, is a computer-gener...
In the stock market, a successful investment requires a good balance bet...
Hyper-parameters optimization (HPO) is vital for machine learning models...
Anomaly detection on attributed graphs is a crucial topic for its practi...
Many applications, e.g., digital twins, rely on sensing data from Intern...
Smart contracts are programs deployed on a blockchain and are immutable ...
With the rapid evolution of metaverse technologies, numerous metaverse
a...
The non-fungible token (NFT) is an emergent type of cryptocurrency that ...
At present, the concept of metaverse has sparked widespread attention fr...
Economic systems play pivotal roles in the metaverse. However, we have n...
Recent studies demonstrate that Graph Neural Networks (GNNs) are vulnera...
Graph neural networks (GNNs) have found successful applications in vario...
With the continuous development of web technology, Web3.0 has attracted ...
As special information carriers containing both structure and feature
in...
This paper reviews and highlights how coding schemes have been used to s...
Recent years have seen a surge in research on dynamic graph representati...
The rapid development of artificial intelligence (AI) technology has ena...
Adapting Deep Learning (DL) techniques to automate non-trivial coding
ac...
We present masked graph autoencoder (MaskGAE), a self-supervised learnin...
Deep graph learning has achieved remarkable progresses in both business ...
In recent years, the rise of deep learning and automation requirements i...
Graph contrastive learning (GCL), as a popular approach to graph
self-su...
Recently, graph convolutional networks (GCNs) have shown to be vulnerabl...
This work concerns the evolutionary approaches to distributed stochastic...
Modern software systems are usually highly configurable, providing users...
In this brief, we conduct a complex-network analysis of the Bitcoin
tran...
This work provides an efficient sampling method for the covariance matri...
Being the largest Initial Coin Offering project, EOSIO has attracted gre...
Recently, many Delegated Proof-of-Stake (DPoS)-based blockchains have be...
Due to the pseudonymous nature of blockchain, various cryptocurrency sys...
Metaverse as the latest buzzword has attracted great attention from both...
Federated learning allows multiple participants to collaboratively train...