Exploring GNN based program embedding technologies for binary related tasks

Author:

Guo Yixin1,Li Pengcheng2,Luo Yingwei1,Wang Xiaolin1,Wang Zhenlin3

Affiliation:

1. Peking University, Beijing, China and Peng Cheng Lab, Shenzhen, China

2. TikTok Inc

3. Michigan Tech

Funder

National Science Foundation of China

National Science Foundation

National Key RD Program of China

PKU-Baidu Fund

Publisher

ACM

Reference56 articles.

1. Miltiadis Allamanis , Hao Peng , and Charles Sutton . 2016 . A convolutional attention network for extreme summarization of source code . In International conference on machine learning. PMLR , 2091--2100. Miltiadis Allamanis, Hao Peng, and Charles Sutton. 2016. A convolutional attention network for extreme summarization of source code. In International conference on machine learning. PMLR, 2091--2100.

2. Uri Alon , Omer Levy , and Eran Yahav . 2019 . code2seq: Generating Sequences from Structured Representations of Code . In International Conference on Learning Representations. https://openreview.net/forum?id=H1gKYo09tX Uri Alon, Omer Levy, and Eran Yahav. 2019. code2seq: Generating Sequences from Structured Representations of Code. In International Conference on Learning Representations. https://openreview.net/forum?id=H1gKYo09tX

3. Uri Alon , Roy Sadaka , Omer Levy , and Eran Yahav . 2020 . Structural language models of code . In International Conference on Machine Learning. PMLR, 245--256 . Uri Alon, Roy Sadaka, Omer Levy, and Eran Yahav. 2020. Structural language models of code. In International Conference on Machine Learning. PMLR, 245--256.

4. code2vec: learning distributed representations of code

5. D. Bahdanau K. Cho and Y. Bengio. 2014. Neural Machine Translation by Jointly Learning to Align and Translate. Computer Science (2014). D. Bahdanau K. Cho and Y. Bengio. 2014. Neural Machine Translation by Jointly Learning to Align and Translate. Computer Science (2014).

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