Beyond Words: Advancing Long-Text Image Generation via Multimodal
  Autoregressive Models
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. To address this, we introduce a novel
text-focused, binary tokenizer optimized for capturing detailed scene text
features. Leveraging our tokenizer, we develop \ModelName, a multimodal
autoregressive model that excels in generating high-quality long-text images
with unprecedented fidelity. Our model offers robust controllability, enabling
customization of text properties such as font style, size, color, and
alignment. Extensive experiments demonstrate that \ModelName~significantly
outperforms SD3.5 Large~sd3 and GPT4o~gpt4o with DALL-E
3~dalle3 in generating long text accurately, consistently, and flexibly.
Beyond its technical achievements, \ModelName~opens up exciting opportunities
for innovative applications like interleaved document and PowerPoint
generation, establishing a new frontier in long-text image generating.
67e4b98039509b0149142daa
Alex Jinpeng Wang
admin_assigned
2025-03-27T10:16:22.358Z
62333a88fd7bb4a39b92d387
https://cdn-avatars.huggingface.co/v1/production/uploads/62333a88fd7bb4a39b92d387/e21AhpcXq37Ak_7rZ-Ca9.png
Alex Jinpeng Wang
user
Awiny
67e4b98039509b0149142dab
Linjie Li
admin_assigned
2025-03-27T10:16:38.209Z
63db16fff03c3d71ef397206
/avatars/bfb7e0d730b7d03302799d5d2828d97d.svg
Linjie Li
user
linjieli222
67e4b98039509b0149142dac
Zhengyuan Yang
admin_assigned
2025-03-27T10:16:44.117Z
630713411801ecc7d2592a7c
/avatars/fb36f69f03421c3a2a7f72ba0858fa60.svg
Zhengyuan Yang
user
zyang39
67e4b98039509b0149142dad
Lijuan Wang
admin_assigned
2025-03-27T10:16:50.812Z
6413521d4e5305c14f22e110
/avatars/a6f8d0573e678f79bc3c0b7897b818ce.svg
Lijuan Wang
user
Lijuan
67e4b98039509b0149142dae
Min Li
Beyond Words: Advancing Long-Text Image Generation via Multimodal
  Autoregressive Models
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. To address this, we introduce a novel
text-focused, binary tokenizer optimized for capturing detailed scene text
features. Leveraging our tokenizer, we develop \ModelName, a multimodal
autoregressive model that excels in generating high-quality long-text images
with unprecedented fidelity. Our model offers robust controllability, enabling
customization of text properties such as font style, size, color, and
alignment. Extensive experiments demonstrate that \ModelName~significantly
outperforms SD3.5 Large~sd3 and GPT4o~gpt4o with DALL-E
3~dalle3 in generating long text accurately, consistently, and flexibly.
Beyond its technical achievements, \ModelName~opens up exciting opportunities
for innovative applications like interleaved document and PowerPoint
generation, establishing a new frontier in long-text image generating.
A multimodal autoregressive model with a novel binary tokenizer outperforms existing systems in generating high-quality long-text images with robust controllability.
autoregressive models diffusion models image tokenizer multimodal autoregressive model text-focused tokenizer high-quality long-text images font style font size color alignment DALL-E 3 SD3.5 Large GPT4o