Improving binary code similarity transformer models by semantics-driven instruction deemphasis X Xu, S Feng, Y Ye, G Shen, Z Su, S Cheng, G Tao, Q Shi, Z Zhang, ... Proceedings of the 32nd ACM SIGSOFT International Symposium on Software …, 2023 | 6 | 2023 |
Lmpa: Improving decompilation by synergy of large language model and program analysis X Xu, Z Zhang, S Feng, Y Ye, Z Su, N Jiang, S Cheng, L Tan, X Zhang arXiv preprint arXiv:2306.02546, 2023 | 5 | 2023 |
CodeArt: Better Code Models by Attention Regularization When Symbols Are Lacking Z Su, X Xu, Z Huang, Z Zhang, Y Ye, J Huang, X Zhang arXiv preprint arXiv:2402.11842, 2024 | 1 | 2024 |
Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases Z Su, X Xu, Z Huang, K Zhang, X Zhang arXiv preprint arXiv:2405.19581, 2024 | | 2024 |
When Dataflow Analysis Meets Large Language Models C Wang, W Zhang, Z Su, X Xu, X Xie, X Zhang arXiv preprint arXiv:2402.10754, 2024 | | 2024 |
Leveraging Generative Models to Recover Variable Names from Stripped Binary X Xu, Z Zhang, Z Su, Z Huang, S Feng, Y Ye, N Jiang, D Xie, S Cheng, ... arXiv preprint arXiv:2306.02546, 2023 | | 2023 |