6 citations · 14 across the 9 of their papers we have counts for
9 papers
ContraLog: Log File Anomaly Detection with Contrastive Learning and Masked Language Modeling
Simon Dietz, Kai Klede, An Nguyen +1
Log files record computational events that reflect system state and behavior, making them a primary source of operational insights in modern computer systems. Automated anomaly det…
iML: Executable, Problem-Grounded, and Broadly Exploratory Code-Driven AutoML
Dat Le, Duc-Cuong Le, Anh-Son Nguyen +4
Automated Machine Learning (AutoML) has improved access to machine learning, yet existing techniques often remain limited in flexibility, transparency, and execution reliability. C…
PatchSeeker: Mapping NVD Records to their Vulnerability-fixing Commits with LLM Generated Commits and Embeddings
Huu Hung Nguyen, Anh Tuan Nguyen, Thanh Le-Cong +8
Software vulnerabilities pose serious risks to modern software ecosystems. While the National Vulnerability Database (NVD) is the authoritative source for cataloging these vulnerab…
Jailbreak Distillation: Renewable Safety Benchmarking
Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5
Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…
Do LLMs Consider Security? An Empirical Study on Responses to Programming Questions
Amirali Sajadi, Binh Le, Anh Nguyen +2
The widespread adoption of conversational LLMs for software development has raised new security concerns regarding the safety of LLM-generated content. Our motivational study outli…
Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++
Anh The Nguyen, Triet Huynh Minh Le, M. Ali Babar
Background: The C and C++ languages hold significant importance in Software Engineering research because of their widespread use in practice. Numerous studies have utilized Machine…
AI-powered Code Review with LLMs: Early Results
Zeeshan Rasheed, Malik Abdul Sami, Muhammad Waseem +5
In this paper, we present a novel approach to improving software quality and efficiency through a Large Language Model (LLM)-based model designed to review code and identify potent…
Envisioning the Next-Generation AI Coding Assistants: Insights & Proposals
Khanh Nghiem, Anh Minh Nguyen, Nghi D. Q. Bui
As a research-product hybrid group in AI for Software Engineering (AI4SE), we present four key takeaways from our experience developing in-IDE AI coding assistants. AI coding assis…
AtomXR: Streamlined XR Prototyping with Natural Language and Immersive Physical Interaction
Alice Cai, Caine Ardayfio, AnhPhu Nguyen +2
As technological advancements in extended reality (XR) amplify the demand for more XR content, traditional development processes face several challenges: 1) a steep learning curve…