4 papers
Chain of World: World Model Thinking in Latent Motion
Fuxiang Yang, Donglin Di, Lulu Tang +6
Vision-Language-Action (VLA) models are a promising path toward embodied intelligence, yet they often overlook the predictive and temporal-causal structure underlying visual dynami…
VisualDAN: Exposing Vulnerabilities in VLMs with Visual-Driven DAN Commands
Aofan Liu, Lulu Tang
Vision-Language Models (VLMs) have garnered significant attention for their remarkable ability to interpret and generate multimodal content. However, securing these models against…
PiCo: Jailbreaking Multimodal Large Language Models via Pictorial Code Contextualization
Aofan Liu, Lulu Tang, Ting Pan +3
Multimodal Large Language Models (MLLMs), which integrate vision and other modalities into Large Language Models (LLMs), significantly enhance AI capabilities but also introduce ne…
Tokenize Anything via Prompting
Ting Pan, Lulu Tang, Xinlong Wang +1
We present a unified, promptable model capable of simultaneously segmenting, recognizing, and captioning anything. Unlike SAM, we aim to build a versatile region representation in…