AI RESEARCH
ICG: Improving Cover Image Generation via MLLM-based Prompting and Personalized Preference Alignment
arXiv CS.CL
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ArXi:2605.27374v1 Announce Type: new Recent advances in multimodal large language models (MLLMs) and diffusion models (DMs) have opened new possibilities for AI-generated content. Yet, personalized cover image generation remains underexplored, despite its critical role in boosting user engagement on digital platforms. We propose ICG, a novel framework that integrates MLLM-based prompting with personalized preference alignment to generate high-quality, contextually relevant covers.