Open Vocabulary Learning on Source Code with a Graph-Structured Cache. ICML 2019. paper Milan Cvitkovic, Badal Singh, Anima Anandkumar. Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks. NeurIPS 2019. paper Yaqin Zhou, Shangqing Liu, Ji...
Codeformer iteratively executes basic block embedding to learn abundant global information and finally uses the GNN to aggregate all the basic blocks of a function. We conducted experiments on the OpenSSL, Clamav and Curl datasets. The evaluation results show that our met...
Then, install the needed dependencies. The code is implemented inPytorch.Note that this has been tested using Python 3.9. #install dependenciespip install numpy scipy matplotlib torch torch-geometric torch-scatter How to run the code Test pretrained nets ...
Binary code similarity detection is used to calculate the code similarity of a pair of binary functions or files, through a certain calculation method and judgment method. It is a fundamental task in the field of computer binary security. Traditional methods of similarity detection usually use graph...
《Improving Code Generation by Training with Natural Language Feedback》(2023) GitHub: github.com/nyu-mll/ILF-for-code-generation [fig5]《WavCaps: A ChatGPT-Assisted Weakly-Labelled Audio Captioning Dataset for Audio-Language Multimodal Research》(2023) GitHub: github.com/XinhaoMei/WavCaps...
Code:未公开 这篇文章是GNN在医学图像中的应用,和前面例子中提到的半监督任务很相似(Sec. 2.1)。每个病人是一个节点,节点特征是CNN得到的图像特征,连接关系根据非图像。 之后利用GCN来训练图,其中一部分病人(节点)是有疾病label的,一部分没有,通过labeled data约束预测无labeled data的疾病类别。 3.1.3 Multi-...
最后，最近还更新了一版文章的code，欢迎大家测试！https://github.com/JiaruiFeng/KP-GNN [1] Justin...
与Seq2Seq模型相比,Graph2Seq模型在广泛的NLP任务中显示出优越的性能,包括神经机器翻译,AMR-to-text、文本摘要、问题生成、KG-to-text、SQL-to-text 、code summarization和语义解析。 基于图的编码器 早期的Graph2Seq方法及其后续工作主要使用一些典型的GNN变体作为图编码器,包括GCN、GGNN、GraphSAGE和GAT。由于NLP...
本文为大家整理了CVPR 2020 图神经网络(GNN)相关的比较有意思的值得阅读的10篇论文,供大家参考—分别是:点云分析、视频描述生成、轨迹预测、场景图生成、视频理解、3D语义分割、指代表达式推理、图像描述生成、图像处理、时空图等方向文章。 1. Grid-GCN for Fast and Scalable Point Cloud Learning...
To train the GNN, we need to define a few hyperparameters before the training process, such as the file names of the graph constructed, the number of layers of GNN models, the training epochs, the optimizer, the optimization parameters, and ...