Interpreters for GNN-Based Vulnerability Detection: Are We There Yet?-Reference-Cited by-同舟云学术

Interpreters for GNN-Based Vulnerability Detection: Are We There Yet?

Published:2023-07-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis
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Author:

Hu Yutao¹,Wang Suyuan¹,Li Wenke¹,Peng Junru²,Wu Yueming³,Zou Deqing¹,Jin Hai¹

Affiliation:

1. Huazhong University of Science and Technology, China

2. Wuhan University, China

3. Nanyang Technological University, Singapore

Funder

National Science Foundation of China

Hubei Province Key R&D Technology Special Innovation Project

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3597926.3598145

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4. Federico Baldassarre and Hossein Azizpour . 2019. Explainability techniques for graph convolutional networks. arXiv preprint arXiv:1905.13686, abs/1905.13686 ( 2019 ), https://doi.org/10.48550/arXiv.1905.13686 10.48550/arXiv.1905.13686 Federico Baldassarre and Hossein Azizpour. 2019. Explainability techniques for graph convolutional networks. arXiv preprint arXiv:1905.13686, abs/1905.13686 (2019), https://doi.org/10.48550/arXiv.1905.13686

5. BGNN4VD: Constructing Bidirectional Graph Neural-Network for Vulnerability Detection

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