1 citations · 1 across the 4 of their papers we have counts for
4 papers
Benign-to-Toxic Jailbreaking: Inducing Harmful Responses from Harmless Prompts
Hee-Seon Kim, Minbeom Kim, Wonjun Lee +2
Optimization-based jailbreaks typically adopt the Toxic-Continuation setting in large vision-language models (LVLMs), following the standard next-token prediction objective. In thi…
Exploiting Vision Encoder Vulnerabilities for Universal Adversarial Perturbations on Large Vision-Language Models
Hee-Seon Kim, Minbeom Kim, Seokil Ham +1
Large Vision-Language Models (LVLMs) have achieved remarkable performance on multimodal tasks but remain highly vulnerable to small adversarial perturbations in input images. Exist…
VideoMamba: Spatio-Temporal Selective State Space Model
Jinyoung Park, Hee-Seon Kim, Kangwook Ko +2
We introduce VideoMamba, a novel adaptation of the pure Mamba architecture, specifically designed for video recognition. Unlike transformers that rely on self-attention mechanisms…
Breaking Temporal Consistency: Generating Video Universal Adversarial Perturbations Using Image Models
Hee-Seon Kim, Minji Son, Minbeom Kim +2
As video analysis using deep learning models becomes more widespread, the vulnerability of such models to adversarial attacks is becoming a pressing concern. In particular, Univers…