54 citations · 61 across the 8 of their papers we have counts for
9 papers
VulnGym: Benchmarking Coding Agents for Repository-Level Vulnerability Detection
Kexing Ji, Jiachen Liu, Enze Hu +7
Recent advances in LLM-based vulnerability detection have shown promising results, while coding agents further extend this capability from isolated code snippets to complete reposi…
Unseen-Codebases-Domain Data Synthesis and Training Based on Code Graphs
Guangsheng Ou, Qiming Zhang, Sirong Chen +9
In the context of newly release software frameworks, large language models (LLMs) often exhibit poor performance and a high rate of hallucination, as they are not exposed to such e…
An Empirical Study of Knowledge Distillation for Code Understanding Tasks
Ruiqi Wang, Zezhou Yang, Cuiyun Gao +2
Pre-trained language models (PLMs) have emerged as powerful tools for code understanding. However, deploying these PLMs in large-scale applications faces practical challenges due t…
Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering
Ruiqi Wang, Jiyu Guo, Cuiyun Gao +3
Recently, large language models (LLMs) have been deployed to tackle various software engineering (SE) tasks like code generation, significantly advancing the automation of SE tasks…
An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities
Zezhou Yang, Sirong Chen, Cuiyun Gao +4
Code generation aims to automatically generate code snippets of specific programming language according to natural language descriptions. The continuous advancements in deep learni…
The Current Challenges of Software Engineering in the Era of Large Language Models
Cuiyun Gao, Xing Hu, Shan Gao +2
With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models,…
Uncovering Weaknesses in Neural Code Generation
Xiaoli Lian, Shuaisong Wang, Jieping Ma +5
Code generation, the task of producing source code from prompts, has seen significant advancements with the advent of pre-trained large language models (PLMs). Despite these achiev…
A Roadmap on Modern Code Review: Challenges and Opportunities
Zezhou Yang, Cuiyun Gao, Zhaoqiang Guo +4
Over the past decade, modern code review (MCR) has been established as a cornerstone of software quality assurance and a vital channel for knowledge transfer within development tea…
Deep Learning Based Code Generation Methods: Literature Review
Zezhou Yang, Sirong Chen, Cuiyun Gao +3
This paper focuses on Code Generation task that aims at generating relevant code fragments according to given natural language descriptions. In the process of software development,…