3 papers
cs.CV2026
CHILD: Human-in-the-Loop OOD Detection for Safe Clinical Deployment
Jinlun Ye, Kaiyue Lu, Runhe Lai +3
Out-of-distribution (OOD) detection is critical for safe deployment of medical AI systems. Recently, test-time adaptation (TTA) has emerged as a new paradigm for OOD detection, aut…
cs.LG2026
Instruction Lens Score: Your Instruction Contributes a Powerful Object Hallucination Detector for Multimodal Large Language Models
Runhe Lai, Xinhua Lu, Yanqi Wu +3
Multimodal large language models (MLLMs) have achieved remarkable progress, yet the object hallucination remains a critical challenge for reliable deployment. In this paper, we pre…
cs.CV2025
Local Background Features Matter in Out-of-Distribution Detection
Jinlun Ye, Zhuohao Sun, Yiqiao Qiu +3
Out-of-distribution (OOD) detection is crucial when deploying deep neural networks in the real world to ensure the reliability and safety of their applications. One main challenge…