3 papers
cs.SE2026
When LLMs Invent Rust Crates: An Empirical Study of Hallucination Patterns and Mitigation
Jieming Zheng, Hao Guan, Yepang Liu
Large Language Models (LLMs) have become powerful tools for code generation, yet they remain prone to hallucinations$\unicode{x2013}$producing plausible but incorrect or fabricated…
cs.SE2026
Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches
Yicheng Tao, Yuante Li, Yao Qin +1
Recent advances in large language models (LLMs) have significantly improved automated code generation. While existing approaches have achieved strong performance at the function an…
cs.CV2025
Backdoor Attack on Vision Language Models with Stealthy Semantic Manipulation
Zhiyuan Zhong, Zhen Sun, Yepang Liu +2
Vision Language Models (VLMs) have shown remarkable performance, but are also vulnerable to backdoor attacks whereby the adversary can manipulate the model's outputs through hidden…