132 citations · 683 across the 107 of their papers we have counts for
20 papers · 1 filter
Efficient Parallel Genetic Algorithm for Perturbed Substructure Optimization in Complex Network
Shanqing Yu, Meng Zhou, Jintao Zhou +5
Evolutionary computing, particularly genetic algorithm (GA), is a combinatorial optimization method inspired by natural selection and the transmission of genetic information, which…
CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models
Yeyuan Wang, Dehong Gao, Bin Li +7
The impressive performance of Large Language Model (LLM) has prompted researchers to develop Multi-modal LLM (MLLM), which has shown great potential for various multi-modal tasks.…
Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification
Xuanze Chen, Jiajun Zhou, Shanqing Yu +1
Graph neural networks excel at graph representation learning but struggle with heterophilous data and long-range dependencies. And graph transformers address these issues through s…
Reassessing Layer Pruning in LLMs: New Insights and Methods
Yao Lu, Hao Cheng, Yujie Fang +6
Although large language models (LLMs) have achieved remarkable success across various domains, their considerable scale necessitates substantial computational resources, posing sig…
RedTest: Towards Measuring Redundancy in Deep Neural Networks Effectively
Yao Lu, Peixin Zhang, Jingyi Wang +3
Deep learning has revolutionized computing in many real-world applications, arguably due to its remarkable performance and extreme convenience as an end-to-end solution. However, d…
Lateral Movement Detection via Time-aware Subgraph Classification on Authentication Logs
Jiajun Zhou, Jiacheng Yao, Xuanze Chen +3
Lateral movement is a crucial component of advanced persistent threat (APT) attacks in networks. Attackers exploit security vulnerabilities in internal networks or IoT devices, exp…
Double Whammy: Stealthy Data Manipulation aided Reconstruction Attack on Graph Federated Learning
Jinyin Chen, Minying Ma, Haibin Zheng +1
Recent research has constructed successful graph reconstruction attack (GRA) on GFL. But these attacks are still challenged in aspects of effectiveness and stealth. To address the…
Rethinking Graph Transformer Architecture Design for Node Classification
Jiajun Zhou, Xuanze Chen, Chenxuan Xie +3
Graph Transformer (GT), as a special type of Graph Neural Networks (GNNs), utilizes multi-head attention to facilitate high-order message passing. However, this also imposes severa…
Network Anomaly Traffic Detection via Multi-view Feature Fusion
Song Hao, Wentao Fu, Xuanze Chen +4
Traditional anomalous traffic detection methods are based on single-view analysis, which has obvious limitations in dealing with complex attacks and encrypted communications. In th…
MDM: Advancing Multi-Domain Distribution Matching for Automatic Modulation Recognition Dataset Synthesis
Dongwei Xu, Jiajun Chen, Yao Lu +5
Recently, deep learning technology has been successfully introduced into Automatic Modulation Recognition (AMR) tasks. However, the success of deep learning is all attributed to th…
Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision
Chenxiang Jin, Jiajun Zhou, Chenxuan Xie +3
The rampant fraudulent activities on Ethereum hinder the healthy development of the blockchain ecosystem, necessitating the reinforcement of regulations. However, multiple imbalanc…
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…
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…
A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models
Yao Lu, Yutao Zhu, Yuqi Li +4
With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for signal classification. Although these models…
Node Injection Attack Based on Label Propagation Against Graph Neural Network
Peican Zhu, Zechen Pan, Keke Tang +3
Graph Neural Network (GNN) has achieved remarkable success in various graph learning tasks, such as node classification, link prediction and graph classification. The key to the su…
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property Prediction
Zeyu Wang, Tianyi Jiang, Yao Lu +4
Recently, few-shot molecular property prediction (FSMPP) has garnered increasing attention. Despite impressive breakthroughs achieved by existing methods, they often overlook the i…
Improving Network Degree Correlation by Degree-preserving Rewiring
Shuo Zou, Bo Zhou, Qi Xuan
Degree correlation is a crucial measure in networks, significantly impacting network topology and dynamical behavior. The degree sequence of a network is a significant characterist…
Exploring the Impact of Dataset Bias on Dataset Distillation
Yao Lu, Jianyang Gu, Xuguang Chen +2
Dataset Distillation (DD) is a promising technique to synthesize a smaller dataset that preserves essential information from the original dataset. This synthetic dataset can serve…
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…
Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry
Zeyu Wang, Tianyi Jiang, Jinhuan Wang +1
Molecular property prediction refers to the task of labeling molecules with some biochemical properties, playing a pivotal role in the drug discovery and design process. Recently,…