3 citations · 3 across the 4 of their papers we have counts for
5 papers
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…
Model-Agnostic Correctness Assessment for LLM-Generated Code via Dynamic Internal Representation Selection
Thanh Trong Vu, Tuan-Dung Bui, Thu-Trang Nguyen +2
Large Language Models (LLMs) have demonstrated impressive capabilities in code generation and are increasingly integrated into the software development process. However, ensuring t…
Correctness Assessment of Code Generated by Large Language Models Using Internal Representations
Tuan-Dung Bui, Thanh Trong Vu, Thu-Trang Nguyen +2
Ensuring the correctness of code generated by Large Language Models (LLMs) presents a significant challenge in AI-driven software development. Existing approaches predominantly rel…
RAMBO: Enhancing RAG-based Repository-Level Method Body Completion
Tuan-Dung Bui, Duc-Thieu Luu-Van, Thanh-Phat Nguyen +3
Code completion is essential in software development, helping developers by predicting code snippets based on context. Among completion tasks, Method Body Completion (MBC) is parti…
Automated Description Generation for Software Patches
Thanh Trong Vu, Tuan-Dung Bui, Thanh-Dat Do +3
Software patches are pivotal in refining and evolving codebases, addressing bugs, vulnerabilities, and optimizations. Patch descriptions provide detailed accounts of changes, aidin…