AI RESEARCH
Bernini: Latent Semantic Planning for Video Diffusion
arXiv CS.CV
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ArXi:2605.22344v1 Announce Type: new Multimodal large language models (MLLMs) and diffusion models have each reached remarkable maturity: MLLMs excel at reasoning over heterogeneous multimodal inputs with strong semantic grounding, while diffusion models synthesize images and videos with photorealistic fidelity. We argue that these two families can be unified through a simple division of labor: MLLMs perform semantic planning, while diffusion models render pixels from high-level semantic guidance and low-level visual features.