5 papers
EDITOR: Effective and Interpretable Prompt Inversion for Text-to-Image Diffusion Models
Mingzhe Li, Kejing Xia, Gehao Zhang +5
Text-to-image generation models~(e.g., Stable Diffusion) have achieved significant advancements, enabling the creation of high-quality and realistic images based on textual descrip…
Token-Budget-Aware LLM Reasoning
Tingxu Han, Zhenting Wang, Chunrong Fang +3
Reasoning is critical for large language models (LLMs) to excel in a wide range of tasks. While methods like Chain-of-Thought (CoT) reasoning and enhance LLM performance by decompo…
MLLM-as-a-Judge for Image Safety without Human Labeling
Zhenting Wang, Shuming Hu, Shiyu Zhao +12
Image content safety has become a significant challenge with the rise of visual media on online platforms. Meanwhile, in the age of AI-generated content (AIGC), many image generati…
Tightening Robustness Verification of MaxPool-based Neural Networks via Minimizing the Over-Approximation Zone
Yuan Xiao, Yuchen Chen, Shiqing Ma +6
The robustness of neural network classifiers is important in the safety-critical domain and can be quantified by robustness verification. At present, efficient and scalable verific…
Continuous Concepts Removal in Text-to-image Diffusion Models
Tingxu Han, Weisong Sun, Yanrong Hu +6
Text-to-image diffusion models have shown an impressive ability to generate high-quality images from input textual descriptions. However, concerns have been raised about the potent…