5 papers
MMOOC: A Comprehensive Benchmark for Out-of-Context Evaluation in Multimodal Large Language Models
Wenjie Zhu, Yabin Zhang, Wenjun Zeng +1
Multimodal Large Language Models (MLLMs) have achieved strong performance on a wide range of vision-language tasks, but often fail under imperfect or shifted contexts. A reliable M…
Dual Distribution Estimation for Zero-shot Noisy Test-Time Adaptation with VLMs
Wenjie Zhu, Yabin Zhang, Liang Xu +3
While test-time adaptation (TTA) empowers vision-language models to adapt without costly retraining, it remains highly vulnerable to out-of-distribution (OOD) outliers prevalent in…
ANTS: Adaptive Negative Textual Space Shaping for OOD Detection via Test-Time MLLM Understanding and Reasoning
Wenjie Zhu, Yabin Zhang, Xin Jin +2
The introduction of negative labels (NLs) has proven effective in enhancing Out-of-Distribution (OOD) detection. However, existing methods often lack an understanding of OOD images…
Knowledge Regularized Negative Feature Tuning of Vision-Language Models for Out-of-Distribution Detection
Wenjie Zhu, Yabin Zhang, Xin Jin +2
Out-of-distribution (OOD) detection is crucial for building reliable machine learning models. Although negative prompt tuning has enhanced the OOD detection capabilities of vision-…
AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models
Yabin Zhang, Lei Zhang
Recent research has shown that pre-trained vision-language models are effective at identifying out-of-distribution (OOD) samples by using negative labels as guidance. However, empl…