22 citations · 51 across the 8 of their papers we have counts for
9 papers
ExplainBench: Evaluating Code Explanations from Agents
Zhiyuan Pan, Sungmin Kang, Imam Nur Bani Yusuf +1
Large Language Model (LLM) agents have seen rapid adoption in software engineering. As agents take a greater role in the actual generation of code, they are making larger changes,…
Code Review Agent Benchmark
Yuntong Zhang, Zhiyuan Pan, Imam Nur Bani Yusuf +3
Software engineering agents have shown significant promise in writing code. As AI agents permeate code writing, and generate huge volumes of code automatically -- the matter of cod…
RustMap: Towards Project-Scale C-to-Rust Migration via Program Analysis and LLM
Xuemeng Cai, Jiakun Liu, Xiping Huang +6
Migrating existing C programs into Rust is increasingly desired, as Rust offers superior memory safety while maintaining C's high performance. However, vastly different features be…
Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs
Imam Nur Bani Yusuf, Lingxiao Jiang
Large language models have demonstrated promising performance across various software engineering tasks. While fine-tuning is a common practice to adapt these models for downstream…
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
Terry Yue Zhuo, Minh Chien Vu, Jenny Chim +30
Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to…
Your Instructions Are Not Always Helpful: Assessing the Efficacy of Instruction Fine-tuning for Software Vulnerability Detection
Imam Nur Bani Yusuf, Lingxiao Jiang
Software, while beneficial, poses potential cybersecurity risks due to inherent vulnerabilities. Detecting these vulnerabilities is crucial, and deep learning has shown promise as…