arXiv 2610.09823 · cs.CV · 2026-10-07
UltraText Bench: A Comprehensive Bilingual Benchmark for Evaluating Visual Text Rendering in Image Generation
Deyuan Liu, Yihao Hu, Jingxuan Zhang, Xingying Li, Jun Xie, Jiacheng Liu, Jungang Li, Yu Huang and 8 more
Westlake University
In latest · #44 2026-W41 #3 Added on 2026-10-21
One-line takeaway
UltraText Bench uses 432 bilingual prompts to evaluate dense visual text rendering in image generators.
UltraText Bench 用 432 条中英双语提示，评测图像生成模型渲染密集文字的能力。
Read on arXiv PDF Hugging Face discussion Code
Topics & disciplines
More on Visual generation
- MaLiang-Harness: A Programmable Path to Image and Video Generation ▲367
- Any Time, Any Space: A World-State-Centric Framework for Agentic Video Generation ▲364
- DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion Models ▲325
- Matrix-Game 4.0: Harnessing Video Models for Real-Time Playable Game Worlds ▲182
- Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation ▲174
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.