8 citations · 19 across the 6 of their papers we have counts for
7 papers
Neuro-Symbolic Indirect-Call Analysis under Opaque Pointers
Kaixuan Li, Bozhi Wu, Jian Zhang +3
Resolving indirect calls is central to call-graph construction for C. Scalable type-based analyses such as MLTA use type information in LLVM IR to associate indirect calls with fun…
Learning More from Less: Exploiting Counterfactuals for Data-Efficient Chart Understanding
Jianzhu Bao, Haozhen Zhang, Kuicai Dong +5
Vision-Language Models (VLMs) have demonstrated remarkable progress in chart understanding, largely driven by supervised fine-tuning (SFT) on increasingly large synthetic datasets.…
Logic-Q: Improving Deep Reinforcement Learning-based Quantitative Trading via Program Sketch-based Tuning
Zhiming Li, Junzhe Jiang, Yushi Cao +5
Deep reinforcement learning (DRL) has revolutionized quantitative trading (Q-trading) by achieving decent performance without significant human expert knowledge. Despite its achiev…
ContraBERT: Enhancing Code Pre-trained Models via Contrastive Learning
Shangqing Liu, Bozhi Wu, Xiaofei Xie +2
Large-scale pre-trained models such as CodeBERT, GraphCodeBERT have earned widespread attention from both academia and industry. Attributed to the superior ability in code represen…
Enhancing Security Patch Identification by Capturing Structures in Commits
Bozhi Wu, Shangqing Liu, Ruitao Feng +3
With the rapid increasing number of open source software (OSS), the majority of the software vulnerabilities in the open source components are fixed silently, which leads to the de…
Unveiling Project-Specific Bias in Neural Code Models
Zhiming Li, Yanzhou Li, Tianlin Li +5
Deep learning has introduced significant improvements in many software analysis tasks. Although the Large Language Models (LLMs) based neural code models demonstrate commendable pe…
Why an Android App is Classified as Malware? Towards Malware Classification Interpretation
Bozhi Wu, Sen Chen, Cuiyun Gao +4
Machine learning (ML) based approach is considered as one of the most promising techniques for Android malware detection and has achieved high accuracy by leveraging commonly-used…