2 citations · 3 across the 7 of their papers we have counts for
7 papers
Enhancing LLM Agent Safety via Causal Influence Prompting
Dongyoon Hahm, Woogyeol Jin, June Suk Choi +2
As autonomous agents powered by large language models (LLMs) continue to demonstrate potential across various assistive tasks, ensuring their safe and reliable behavior is crucial…
What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs
Sangyeop Kim, Yohan Lee, Yongwoo Song +1
We investigate long-context vulnerabilities in Large Language Models (LLMs) through Many-Shot Jailbreaking (MSJ). Our experiments utilize context length of up to 128K tokens. Throu…
Silent Branding Attack: Trigger-free Data Poisoning Attack on Text-to-Image Diffusion Models
Sangwon Jang, June Suk Choi, Jaehyeong Jo +2
Text-to-image diffusion models have achieved remarkable success in generating high-quality contents from text prompts. However, their reliance on publicly available data and the gr…
DiffExp: Efficient Exploration in Reward Fine-tuning for Text-to-Image Diffusion Models
Daewon Chae, June Suk Choi, Jinkyu Kim +1
Fine-tuning text-to-image diffusion models to maximize rewards has proven effective for enhancing model performance. However, reward fine-tuning methods often suffer from slow conv…
DiffusionGuard: A Robust Defense Against Malicious Diffusion-based Image Editing
June Suk Choi, Kyungmin Lee, Jongheon Jeong +3
Recent advances in diffusion models have introduced a new era of text-guided image manipulation, enabling users to create realistic edited images with simple textual prompts. Howev…
Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models
Sangwon Jang, Jaehyeong Jo, Kimin Lee +1
Text-to-image diffusion models have shown remarkable success in generating personalized subjects based on a few reference images. However, current methods often fail when generatin…
InstructBooth: Instruction-following Personalized Text-to-Image Generation
Daewon Chae, Nokyung Park, Jinkyu Kim +1
Personalizing text-to-image models using a limited set of images for a specific object has been explored in subject-specific image generation. However, existing methods often face…