This is the source code of our solutions in CCF BDCI 2022 competition held on DataFountain. We introduce advanced miner and loss algorithms from Deep Metric Learning into Binary Code Similarity Detection.
Python 3.10.4
pytorch 1.12.1 (py3.10_cuda10.2_cudnn7.6.5_0)
pytorch-lightning 1.7.3
torch-geometric(PyG) 2.1.0
pytorch-metric-learning 1.5.2
scikit-learn 1.1.1
bash train.sh && bash test.sh
Our model records are in model/lstm_gatedgcn-e/version_0
.
Model | Test MAP |
---|---|
Norm weighted miner + Triplet loss | 0.855586 |
MS miner + Triplet loss | 0.883205 |
MS miner + MS loss (Ours) | 0.922685 |