1 code implementation • 26 Feb 2024 • Hao Wang, Zeyu Gao, Chao Zhang, Zihan Sha, Mingyang Sun, Yuchen Zhou, Wenyu Zhu, Wenju Sun, Han Qiu, Xi Xiao
At the core, our approach boosts superior transfer learning capabilities by effectively aligning binary code with their semantics explanations (in natural language), resulting a model able to generate better embeddings for binary code.
1 code implementation • 21 Nov 2023 • Zeyu Gao, Hao Wang, Yuchen Zhou, Wenyu Zhu, Chao Zhang
Given the significant successes of large language models (LLMs) in various tasks, there is growing anticipation of their efficacy in vulnerability detection.
1 code implementation • 24 Aug 2023 • Wenyu Zhu, Hao Wang, Yuchen Zhou, JiaMing Wang, Zihan Sha, Zeyu Gao, Chao Zhang
By feeding explicit knowledge as additional inputs to the Transformer, and fusing implicit knowledge with a novel pre-training task, kTrans provides a new perspective to incorporating domain knowledge into a Transformer framework.
no code implementations • 9 Jan 2023 • Huanyu Bian, Zhilong Jia, Menghan Dou, Yuan Fang, Lei LI, Yiming Zhao, Hanchao Wang, Zhaohui Zhou, Wei Wang, Wenyu Zhu, Ye Li, Yang Yang, Weiming Zhang, Nenghai Yu, Zhaoyun Chen, Guoping Guo
Therefore, based on VQNet 1. 0, we further propose VQNet 2. 0, a new generation of unified classical and quantum machine learning framework that supports hybrid optimization.
1 code implementation • 2 Nov 2021 • Wenyu Zhu, Zhiyao Feng, Zihan Zhang, Jianjun Chen, Zhijian Ou, Min Yang, Chao Zhang
Recovering binary programs' call graphs is crucial for inter-procedural analysis tasks and applications based on them. transfer One of the core challenges is recognizing targets of indirect calls (i. e., indirect callees).