1 citations · 1 across the 3 of their papers we have counts for
6 papers
On the Effectiveness of Training Data Optimization for LLM-based Code Generation: An Empirical Study
Shiqi Kuang, Zhao Tian, Tao Xiao +2
Large language models (LLMs) have achieved remarkable progress in code generation, largely driven by the availability of high-quality code datasets for effective training. To furth…
Issue-Oriented Agent-Based Framework for Automated Review Comment Generation
Shuochuan Li, Dong Wang, Patanamon Thongtanunam +3
Code review (CR) is a crucial practice for ensuring software quality. Various automated review comment generation techniques have been proposed to streamline the labor-intensive pr…
Clarifying Semantics of In-Context Examples for Unit Test Generation
Chen Yang, Lin Yang, Ziqi Wang +3
Recent advances in large language models (LLMs) have enabled promising performance in unit test generation through in-context learning (ICL). However, the quality of in-context exa…
On the Evaluation of Large Language Models in Multilingual Vulnerability Repair
Dong wang, Junji Yu, Honglin Shu +4
Various Deep Learning-based approaches with pre-trained language models have been proposed for automatically repairing software vulnerabilities. However, these approaches are limit…
A Survey of Reinforcement Learning for Software Engineering
Dong Wang, Hanmo You, Lingwei Zhu +6
Reinforcement Learning (RL) has emerged as a powerful paradigm for sequential decision-making and has attracted growing interest across various domains, particularly following the…
A Preliminary Study of Large Language Models for Multilingual Vulnerability Detection
Junji Yu, Honglin Shu, Michael Fu +4
Deep learning-based approaches, particularly those leveraging pre-trained language models (PLMs), have shown promise in automated software vulnerability detection. However, existin…