49 citations · 135 across the 18 of their papers we have counts for
6 papers · 1 filter
Retrieval-Augmented Prompt for OOD Detection
Ruisong Han, Zongbo Han, Jiahao Zhang +2
Out-of-Distribution (OOD) detection is crucial for the reliable deployment of machine learning models in-the-wild, enabling accurate identification of test samples that differ from…
Hallucination of Multimodal Large Language Models: A Survey
Zechen Bai, Pichao Wang, Tianjun Xiao +4
This survey presents a comprehensive analysis of the phenomenon of hallucination in multimodal large language models (MLLMs), also known as Large Vision-Language Models (LVLMs), wh…
Skip \n: A Simple Method to Reduce Hallucination in Large Vision-Language Models
Zongbo Han, Zechen Bai, Haiyang Mei +3
Recent advancements in large vision-language models (LVLMs) have demonstrated impressive capability in visual information understanding with human language. Despite these advances,…
ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection
Yichen Bai, Zongbo Han, Changqing Zhang +3
Out-of-distribution (OOD) detection methods often exploit auxiliary outliers to train model identifying OOD samples, especially discovering challenging outliers from auxiliary outl…
Semantic Equivariant Mixup
Zongbo Han, Tianchi Xie, Bingzhe Wu +2
Mixup is a well-established data augmentation technique, which can extend the training distribution and regularize the neural networks by creating ''mixed'' samples based on the la…
Uncertainty-Aware Multi-View Representation Learning
Yu Geng, Zongbo Han, Changqing Zhang +1
Learning from different data views by exploring the underlying complementary information among them can endow the representation with stronger expressive ability. However, high-dim…