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.CV2026
Detecting Performance Degradation under Data Shift in Pathology Vision-Language Model
Hao Guan, Li Zhou
Vision-Language Models have demonstrated strong potential in medical image analysis and disease diagnosis. However, after deployment, their performance may deteriorate when the inp…
cs.AI2025
Keeping Medical AI Healthy and Trustworthy: A Review of Detection and Correction Methods for System Degradation
Hao Guan, David Bates, Li Zhou
Artificial intelligence (AI) is increasingly integrated into modern healthcare, offering powerful support for clinical decision-making. However, in real-world settings, AI systems…