Does Unification Come at a Cost? Uni-SafeBench: A Safety Benchmark for Unified Multimodal Large Models

This paper introduces Uni-SafeBench, a new safety benchmark designed to evaluate unified multimodal large models. It investigates the potential costs associated with the unification of different modalities in large AI models, particularly concerning safety and robustness. The research aims to identify and measure novel safety risks that may emerge from such integrated architectures, providing a critical tool for developers to build more secure and reliable multimodal AI systems for various real-world applications.