29 citations · 101 across the 38 of their papers we have counts for
3 papers · 1 filter
VRPTEST: Evaluating Visual Referring Prompting in Large Multimodal Models
Zongjie Li, Chaozheng Wang, Chaowei Liu +4
With recent advancements in Large Multimodal Models (LMMs) across various domains, a novel prompting method called visual referring prompting has emerged, showing significant poten…
InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models
Xunguang Wang, Zhenlan Ji, Pingchuan Ma +3
Large vision-language models (LVLMs) have demonstrated their incredible capability in visual question answering. However, this rich visual interaction also makes LVLMs vulnerable t…
Explain Any Concept: Segment Anything Meets Concept-Based Explanation
Ao Sun, Pingchuan Ma, Yuanyuan Yuan +1
EXplainable AI (XAI) is an essential topic to improve human understanding of deep neural networks (DNNs) given their black-box internals. For computer vision tasks, mainstream pixe…