Duplicate from lioooox/T2I-CoReBench-Images

Co-authored-by: Ouxiang Li <lioooox@users.noreply.huggingface.co>

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README.md

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+---
+license: apache-2.0
+task_categories:
+- text-to-image
+language:
+- en
+tags:
+- Benchmark
+- Evaluation
+- Diffusion Models
+- Autoregressive Models
+- Closed-Source Models
+size_categories:
+- 100K<n<1M
+---
+
+# T2I-CoReBench-Images
+
+## 📖 Overview
+**T2I-CoReBench-Images** is the companion image dataset of [T2I-CoReBench](https://huggingface.co/datasets/lioooox/T2I-CoReBench). It contains images generated using **1,080 challenging prompts**, covering both **composition** and **reasoning** scenarios undere **real-world complexities**.
+
+This dataset is designed to evaluate how well current Text-to-Image (T2I) models can not only *paint* (produce visually consistent outputs) but also *think* (perform reasoning over causal chains, object relations, and logical consistency).  
+
+- 📄 **Paper**: [*Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?*](https://arxiv.org/abs/2509.03516)  
+- 🌐 **Project Page**: [t2i-corebench.github.io](https://t2i-corebench.github.io)  
+- 🤗 **Benchmark Dataset**: [T2I-CoReBench](https://huggingface.co/datasets/lioooox/T2I-CoReBench)  
+
+---
+
+## 📊 Dataset Contents
+- **1,080 prompts** (aligned with T2I-CoReBench) and **4 images per prompt per model**
+- **38 Evaluated T2I models** included (see list below)  
+- **Total images:** (1,080 Prompts × 4 Images × 38 Models) = **164,160** Images
+
+---
+
+### 📌 Models Included
+| Category | Models |
+|----------|--------|
+| **Diffusion Models** | SD-3-Medium, SD-3.5-Medium, SD-3.5-Large, FLUX.1-schnell, FLUX.1-dev, FLUX.1-Krea-dev, FLUX.2-dev, FLUX.2-klein-4B, FLUX.2-klein-9B, PixArt-$\alpha$, PixArt-$\Sigma$, HiDream-I1, Qwen-Image, Qwen-Image-2512, HunyuanImage-3.0, Z-Image-Turbo, LongCat-Image |
+| **Autogressive Models** | Infinity-8B and GoT-R1-7B |
+| **Unified Models** | BAGEL, BAGEL w/ Think, show-o2-1.5B, show-o2-7B, Janus-Pro-1B, Janus-Pro-7B, BLIP3o-4B, BLIP3o-8B, OmniGen2-7B |
+| **Closed-Source Models** | Seedream 3.0, Seedream 4.0, Seedream 4.5, Gemini 2.0 Flash, Nano Banana, Nano Banana Pro, Imagen 4, Imagen 4 Ultra, GPT-Image (GPT-4o), GPT-Image-1.5 |
+
+---
+
+## 📜 Citation
+If you find this dataset useful, please cite our paper:
+
+```bibtex
+@article{li2025easier,
+  title={Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?},
+  author={Li, Ouxiang and Wang, Yuan and Hu, Xinting and Huang, Huijuan and Chen, Rui and Ou, Jiarong and Tao, Xin and Wan, Pengfei and Feng, Fuli},
+  journal={arXiv preprint arXiv:2509.03516},
+  year={2025}
+}