1 citations · 2 across the 5 of their papers we have counts for
6 papers · 1 filter
On the Adversarial Robustness of Multimodal LLM Judges
Zihan Wang, Guansong Pang, Zelin Liu +3
Multimodal Large Language Models (MLLMs) are increasingly used as automated judges, e.g., for image quality and safety assessment. However, their adversarial robustness remains lar…
MTAttack: Multi-Target Backdoor Attacks against Large Vision-Language Models
Zihan Wang, Guansong Pang, Wenjun Miao +2
Recent advances in Large Visual Language Models (LVLMs) have demonstrated impressive performance across various vision-language tasks by leveraging large-scale image-text pretraini…
Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
Wenjun Miao, Guansong Pang, Jin Zheng +1
One key challenge in Out-of-Distribution (OOD) detection is the absence of ground-truth OOD samples during training. One principled approach to address this issue is to use samples…
OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning
Wenjun Miao, Guansong Pang, Trong-Tung Nguyen +3
Class incremental learning (CIL) aims to learn a model that can not only incrementally accommodate new classes, but also maintain the learned knowledge of old classes. Out-of-distr…
Learning Transferable Negative Prompts for Out-of-Distribution Detection
Tianqi Li, Guansong Pang, Xiao Bai +2
Existing prompt learning methods have shown certain capabilities in Out-of-Distribution (OOD) detection, but the lack of OOD images in the target dataset in their training can lead…
Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning
Wenjun Miao, Guansong Pang, Tianqi Li +2
Existing out-of-distribution (OOD) methods have shown great success on balanced datasets but become ineffective in long-tailed recognition (LTR) scenarios where 1) OOD samples are…