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07/07/2023
Unveiling the Potential of Knowledge-Prompted ChatGPT for Enhancing Drug Trafficking Detection on Social Media
Social media platforms such as Instagram and Twitter have emerged as cri...
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04/02/2023
Graph Mining for Cybersecurity: A Survey
The explosive growth of cyber attacks nowadays, such as malware, spam, a...
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11/19/2022
Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning
Graph Neural Networks (GNNs) have drawn significant attentions over the ...
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11/12/2022
Self-Supervised Graph Structure Refinement for Graph Neural Networks
Graph structure learning (GSL), which aims to learn the adjacency matrix...
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10/06/2022
Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering
A common thread of open-domain question answering (QA) models employs a ...
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10/05/2022
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
Self-supervised learning (SSL) for graph neural networks (GNNs) has attr...
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10/01/2022
Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning
Even pruned by the state-of-the-art network compression methods, Graph N...
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10/01/2022
Multi-objective Deep Data Generation with Correlated Property Control
Developing deep generative models has been an emerging field due to the ...
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09/30/2022
Contrastive Graph Few-Shot Learning
Prevailing deep graph learning models often suffer from label sparsity i...
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09/16/2022
Adversarial Cross-View Disentangled Graph Contrastive Learning
Graph contrastive learning (GCL) is prevalent to tackle the supervision ...
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02/28/2022
Disentangled Spatiotemporal Graph Generative Models
Spatiotemporal graph represents a crucial data structure where the nodes...
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02/18/2022
Black-box Node Injection Attack for Graph Neural Networks
Graph Neural Networks (GNNs) have drawn significant attentions over the ...
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12/08/2021
Adaptive Kernel Graph Neural Network
Graph neural networks (GNNs) have demonstrated great success in represen...
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10/26/2021
Heterogeneous Temporal Graph Neural Network
Graph neural networks (GNNs) have been broadly studied on dynamic graphs...
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10/25/2021
Gophormer: Ego-Graph Transformer for Node Classification
Transformers have achieved remarkable performance in a myriad of fields ...
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10/08/2021
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
Social recommendation task aims to predict users' preferences over items...
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08/19/2021
Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multilabel Learning Approach
Social media such as Instagram and Twitter have become important platfor...
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08/18/2021
Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion
Illicit drug trafficking via social media sites such as Instagram has be...
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05/18/2021
CoTexT: Multi-task Learning with Code-Text Transformer
We present CoTexT, a pre-trained, transformer-based encoder-decoder mode...
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11/30/2020
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Heterogeneous graphs (HGs) also known as heterogeneous information netwo...
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06/09/2020
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Disentangled representation learning has recently attracted a significan...
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05/24/2020
SoK: Arms Race in Adversarial Malware Detection
Malicious software (malware) is a major cyber threat that shall be tackl...
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04/15/2020
Enhancing Deep Neural Networks Against Adversarial Malware Examples
Machine learning based malware detection is known to be vulnerable to ad...
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03/27/2020
α-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19
The novel coronavirus and its deadly outbreak have posed grand challenge...
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12/06/2019
Hyperbolic Graph Attention Network
Graph neural network (GNN) has shown superior performance in dealing wit...
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09/10/2019
Temporal Network Embedding with Micro- and Macro-dynamics
Network embedding aims to embed nodes into a low-dimensional space, whil...
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12/19/2018
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge
Malware continues to be a major cyber threat, despite the tremendous eff...
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11/02/2018
