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Publications
MOSSBench: Is Your Multimodal Language Model Oversensitive to Safe Queries?
Xirui Li*, Hengguang Zhou*, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Cho-Jui Hsieh
Under Review MLLM Safety Oversensitivity
Large Language Models are Interpretable Learners
Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit Dhillon
Google Neuro-Symbolic Program MLLM Prompt Optimization Benchmark Interpretability
The Crystal Ball Hypothesis in Diffusion Models: Anticipating Object Positions from Initial Noise
Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Boqing Gong, Cho-Jui Hsieh, Minhao Cheng
Stable Diffusion Controllable Generation Detection Bias Dataset
DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers
Xirui Li, Ruochen Wang, Minhao Cheng, Tianyi Zhou, Cho-Jui Hsieh
Safety Trustworthy AI Jailbreak
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Ruochen Wang*, Sohyun An*, Minhao Cheng, Tianyi Zhou, Sung Ju Hwang, Cho-Jui Hsieh
ICML2024 Mixture-of-Experts Prompt Optimization
MuLan: Multimodal-LLM Agent for Progressive Multi-object Diffusion
Sen Li, Ruochen Wang, Cho-Jui Hsieh, Minhao Cheng, Tianyi Zhou
Stable Diffusion Controllable Generation Interactive Editing
Understanding the Impact of Negative Prompts: When
and How Do They Take Effect?
Yuanhao Ban, Ruochen Wang, Tianyi Zhou, Minhao Cheng, Boqing Gong, Cho-Jui Hsieh
Stable Diffusion Controllable Generation Inpainting Image Editing
On Discrete Prompt Optimization for Diffusion Models
Ruochen Wang, Ting Liu, Cho-Jui Hsieh, Boqing Gong
ICML2024 Google Deepmind Stable Diffusion Multimodal Alignment Prompt Optimization
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