6 papers · 1 filter
ContextNav: Towards Agentic Multimodal In-Context Learning
Honghao Fu, Yuan Ouyang, Kai-Wei Chang +3
Recent advances demonstrate that multimodal large language models (MLLMs) exhibit strong multimodal in-context learning (ICL) capabilities, enabling them to adapt to novel vision-l…
Text Speaks Louder than Vision: ASCII Art Reveals Textual Biases in Vision-Language Models
Zhaochen Wang, Bryan Hooi, Yiwei Wang +3
Vision-language models (VLMs) have advanced rapidly in processing multimodal information, but their ability to reconcile conflicting signals across modalities remains underexplored…
MIRAGE: Multimodal Immersive Reasoning and Guided Exploration for Red-Team Jailbreak Attacks
Wenhao You, Bryan Hooi, Yiwei Wang +5
While safety mechanisms have significantly progressed in filtering harmful text inputs, MLLMs remain vulnerable to multimodal jailbreaks that exploit their cross-modal reasoning ca…
Making Every Step Effective: Jailbreaking Large Vision-Language Models Through Hierarchical KV Equalization
Shuyang Hao, Yiwei Wang, Bryan Hooi +4
In the realm of large vision-language models (LVLMs), adversarial jailbreak attacks serve as a red-teaming approach to identify safety vulnerabilities of these models and their ass…
Tit-for-Tat: Safeguarding Large Vision-Language Models Against Jailbreak Attacks via Adversarial Defense
Shuyang Hao, Yiwei Wang, Bryan Hooi +5
Deploying large vision-language models (LVLMs) introduces a unique vulnerability: susceptibility to malicious attacks via visual inputs. However, existing defense methods suffer fr…
Lost in Edits? A -Compass for AIGC Provenance
Wenhao You, Bryan Hooi, Yiwei Wang +5
Recent advancements in diffusion models have driven the growth of text-guided image editing tools, enabling precise and iterative modifications of synthesized content. However, as…