Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models

Understand

Recent advancements in autoregressive and diffusion models have led to strong performance in image generation with short scene text words.

• However, generating coherent, long-form text in images, such as paragraphs in slides or documents, remains a major challenge for current generative models.
• We present the first work specifically focused on long text image generation, addressing a critical gap in existing text-to-image systems that typically handle only brief phrases or single sentences.
• Through comprehensive analysis of state-of-the-art autoregressive generation models, we identify the image tokenizer as a critical bottleneck in text generating quality.