Cuiyun Gao

Listening to Users' Voice: Automatic Summarization of Helpful App Reviews

2022 · IEEE Transactions on Reliability

App reviews are crowdsourcing knowledge of user experience with the apps, providing valuable information for app release planning, such as major bugs to fix and important features to add. There exist prior explorations on app …

Meta-Path Based Attentional Graph Learning Model for Vulnerability Detection

2022 · arXiv (Cornell University)

In recent years, deep learning (DL)-based methods have been widely used in code vulnerability detection. The DL-based methods typically extract structural information from source code, e.g., code structure graph, and adopt neural networks such as …

Exploring Multi-Lingual Bias of Large Code Models in Code Generation

2024 · arXiv (Cornell University)

Code generation aims to synthesize code and fulfill functional requirements based on natural language (NL) specifications, which can greatly improve development efficiency. In the era of large language models (LLMs), large code models (LCMs) have …

Imperfect Code Generation: Uncovering Weaknesses in Automatic Code Generation by Large Language Models

2024

The task of code generation has received significant attention in recent years, especially when the pre-trained large language models (LLMs) for code have consistently achieved state-of-the-art performance. However, there is currently a lack of a …

Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware

2025 · arXiv (Cornell University)

Application Programming Interfaces (APIs) are crucial in modern software development. Large Language Models (LLMs) assist in automated code generation but often struggle with API hallucination, including invoking non-existent APIs and misusing existing ones in practical …