4 papers
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…
An Empirical Study on Capability of Large Language Models in Understanding Code Semantics
Thu-Trang Nguyen, Thanh Trong Vu, Hieu Dinh Vo +1
Large Language Models for Code (code LLMs) have demonstrated remarkable performance across various software engineering (SE) tasks, increasing the application of code LLMs in softw…
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…