most citedSingle Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning

1 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR20241 cited

Facilitating Feature and Topology Lightweighting: An Ethereum Transaction Graph Compression Method for Malicious Account Detection

Jiajun Zhou, Xuanze Chen, Shengbo Gong +4

Ethereum has become one of the primary global platforms for cryptocurrency, playing an important role in promoting the diversification of the financial ecosystem. However, the rela…

cs.CR2024

Dual-view Aware Smart Contract Vulnerability Detection for Ethereum

Jiacheng Yao, Maolin Wang, Wanqi Chen +4

The wide application of Ethereum technology has brought technological innovation to traditional industries. As one of Ethereum's core applications, smart contracts utilize diverse…

cs.CL2024

General2Specialized LLMs Translation for E-commerce

Kaidi Chen, Ben Chen, Dehong Gao +6

Existing Neural Machine Translation (NMT) models mainly handle translation in the general domain, while overlooking domains with special writing formulas, such as e-commerce and le…

cs.LG2024

A Federated Parameter Aggregation Method for Node Classification Tasks with Different Graph Network Structures

Hao Song, Jiacheng Yao, Zhengxi Li +6

Over the past few years, federated learning has become widely used in various classical machine learning fields because of its collaborative ability to train data from multiple sou…

cs.SI20231 cited

MONA: An Efficient and Scalable Strategy for Targeted k-Nodes Collapse

Yuqian Lv, Bo Zhou, Jinhuan Wang +2

The concept of k-core plays an important role in measuring the cohesiveness and engagement of a network. And recent studies have shown the vulnerability of k-core under adversarial…

cs.LG20231 cited

Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning

Dayuan Chen, Jian Zhang, Yuqian Lv +5

Graph neural networks (GNNs) have achieved remarkable success in various real-world applications. However, recent studies highlight the vulnerability of GNNs to malicious perturbat…