54 citations · 54 across the 6 of their papers we have counts for
5 papers · 1 filter
On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation
Jia Feng, Zhanyue Qin, Cuiyun Gao +4
Repository-level code intelligence tasks require large language models (LLMs) to process long, multi-file contexts. Such inputs introduce three challenges: crucial context can be o…
Benchmarking Code LLM-as-a-Judge via Constrained Perturbation and Calibration
Ruiqi Wang, Xinchen Wang, Cuiyun Gao +3
Code from LLM-assisted development may contain defects like API hallucinations, motivating the development of code evaluation metrics to assess such code before deployment. As conv…
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…
Game Rewards Vulnerabilities: Software Vulnerability Detection with Zero-Sum Game and Prototype Learning
Xin-Cheng Wen, Cuiyun Gao, Xinchen Wang +3
Recent years have witnessed a growing focus on automated software vulnerability detection. Notably, deep learning (DL)-based methods, which employ source code for the implicit acqu…