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MCBench is a new benchmark for assessing the safety of omnimodal large language models across vision, audio, and text modalities. It includes 1196 scenarios and finds current models struggle with cross-modal safety reasoning.
This paper proposes a novel approach that conditions diffusion models on Multimodal Large Language Models (MLLMs) for subject-driven image generation, using VAE-based identity conditioning and a Dual Layer Aggregation module to improve both semantic understanding and identity preservation while mitigating copy-paste artifacts.