8 papers · 1 filter
How Reasoning Shapes Social Bias in LLM-Generated Code?
Weifeng Sun, Jieke Shi, Zhou Yang +4
Large language models (LLMs) are increasingly used for code generation, yet generated programs may exhibit social bias through unfair or differential treatment of sensitive demogra…
SciCodePile: A 128GB Corpus and Executable Benchmark for Challenging Scientific Code Generation
Weifeng Sun, Ye Fan, Yuchen Chen +6
Large language models (LLMs) excel at general-purpose code generation, yet how well they handle scientific code remains an open question. Existing datasets and benchmarks are limit…
Probing Privacy Leaks in LLM-based Code Generation via Test Generation
Yifei Ge, Zhenpeng Chen, Weisong Sun +7
The widespread availability of large-scale code datasets has fueled the rapid development of large language models (LLMs) for code-related tasks. These datasets may include sensiti…
PuzzleMark: Implicit Jigsaw Learning for Robust Code Dataset Watermarking in Neural Code Completion Models
Haocheng Huang, Yuchen Chen, Weisong Sun +5
Constructing and curating high-quality code datasets requires significant resources, making them valuable intellectual property. Unfortunately, these datasets currently face severe…
Security of Language Models for Code: A Systematic Literature Review
Yuchen Chen, Weisong Sun, Chunrong Fang +7
Language models for code (CodeLMs) have emerged as powerful tools for code-related tasks, outperforming traditional methods and standard machine learning approaches. However, these…
Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based on Code Naturalness
Weisong Sun, Yuchen Chen, Mengzhe Yuan +6
Neural code models (NCMs) have demonstrated extraordinary capabilities in code intelligence tasks. Meanwhile, the security of NCMs and NCMs-based systems has garnered increasing at…