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Adversarial Attacks on Graph Embeddings Based on Text Datasets

This repository hosts the Master's Thesis project "Adversarial Attacks on Graph Embeddings Based on Text Dataset" from the Computer Science and Engineering (CSE) program at Washington University in St. Louis (WashU). It includes the thesis paper, defense slides, and a link to the AAAI workshop paper version.

Contents

  • Thesis Paper: Detailed research documentation.
  • Defense Slides: Presentation for thesis defense.
  • AAAI Workshop Paper: View the paper.
  • Code repo: Code.

Overview

The project explores adversarial attacks on graph embeddings in text datasets, aiming to identify and mitigate vulnerabilities in graph-based text analysis methods.

Contact

For inquiries or further discussion, please feel free to reach out.

Thank you for exploring our research on improving the robustness of graph embeddings in text processing.