Upload README.md

README.md

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+<div align="center">
+    <a href="https://arxiv.org/abs/2512.09271"><img src="https://img.shields.io/badge/Arxiv-preprint-red"></a>
+    <a href="https://welldky.github.io/LongT2IBench-Homepage/"><img src="https://img.shields.io/badge/Homepage-green"></a>
+    <!-- <a href="https://huggingface.co/spaces/orpheus0429/FGResQ"><img src="https://img.shields.io/badge/?¤?%20Hugging%20Face-Spaces-blue"></a> -->
+    <a href='https://github.com/yzc-ippl/LongT2IBench/stargazers'><img src='https://img.shields.io/github/stars/yzc-ippl/LongT2IBench.svg?style=social'></a>
+
+</div>
+
+<h1 align="center">LongT2IBench: A Benchmark for Evaluating Long Text-to-Image Generation with Graph-structured Annotations</h1>
+
+<div align="center">
+    <a href="https://github.com/yzc-ippl/" target="_blank">Zhichao Yang</a><sup>1</sup>,
+    <a href="https://github.com/welldky" target="_blank">Tianjiao Gu</a><sup>1</sup>,
+    <a href="https://github.com/satan-7" target="_blank">Jianjie Wang</a><sup>1</sup>,
+    <a href="https://github.com/Guapicat0" target="_blank">Feiyu Lin</a><sup>1</sup>,
+    <a href="https://github.com/sxfly99" target="_blank">Xiangfei Sheng</a><sup>1</sup>,
+    <a href="https://faculty.xidian.edu.cn/cpf/" target="_blank">Pengfei Chen</a><sup>1*</sup>,
+    <a href="https://web.xidian.edu.cn/ldli/" target="_blank">Leida Li</a><sup>1,2*</sup>
+</div>
+
+<div align="center">
+  <sup>1</sup>School of Artificial Intelligence, Xidian University
+  <br>
+  <sup>2</sup>State Key Laboratory of Electromechanical Integrated Manufacturing of High-Performance Electronic Equipments, Xidian University
+</div>
+
+<div align="center">
+<sup>*</sup>Corresponding author
+</div>
+
+<div align="center">
+  <img src="LongT2IBench.png" width="800"/>
+</div>
+
+<div style="font-family: sans-serif; margin-bottom: 2em;">
+    <h2 style="border-bottom: 1px solid #eaecef; padding-bottom: 0.3em; margin-bottom: 1em;">News</h2>
+    <ul style="list-style-type: none; padding-left: 0;">
+        <li style="margin-bottom: 0.8em;">
+            <strong>[2025-12-21]</strong> The training code has been released.
+        </li>
+        <li style="margin-bottom: 0.8em;">
+            <strong>[2025-12-09]</strong> The data and pre-trained models have been released.
+        </li>
+        <li style="margin-bottom: 0.8em;">
+            <strong>[2025-11-08]</strong> Our paper, "LongT2IBench: A Benchmark for Evaluating Long Text-to-Image Generation with Graph-structured Annotations", has been accepted for an oral presentation at AAAI 2026!
+        </li>
+    </ul>
+</div>
+
+## Quick Start
+
+This guide will help you get started with the LongT2IBench inference code.
+
+### 1. Installation
+
+First, clone the repository and install the required dependencies.
+
+```bash
+git clone https://github.com/yzc-ippl/LongT2IBench.git
+cd LongT2IBench
+pip install -r requirements.txt
+```
+
+### 2. Download Pre-trained Weights and Dataset
+
+##### Prepare Pre-trained Weights
+
+You can download the pre-trained model weights of <strong>[LongT2IExpert]</strong> from the following link: [**(Baidu Netdisk)**](https://pan.baidu.com/s/1Ltj77l31hyBkn6nLtYctnQ?pwd=i8ug)
+
+Place the downloaded files in the `weights` directory.
+
+- ``./weights/LongT2IBench-checkpoints``: The main model for generation and scoring.
+
+Create the `weights` directory if it doesn't exist and place the files inside.
+
+##### Prepare Datasets
+
+You can download the dataset of <strong>[LongPrompt-3K]</strong> and <strong>[LongT2IBench-14K]</strong> from the following link: [**(Baidu Netdisk)**](https://pan.baidu.com/s/1M_tE9EfA2s0Vn7l9r0GebA?pwd=7b6d)
+
+Place the downloaded files in the `data` directory.
+
+Create the `data` directory if it doesn't exist and place the files inside.
+
+```
+LongT2IBench/
+|-- weights/
+|   |-- LongT2IBench-checkpoints
+|   |   |-- config.json
+|   |   |-- ...
+|   |-- Qwen2.5-VL-7B-Instruct
+|   |   |-- config.json
+|   |   |-- ...
+|-- data/
+|   |-- imgs
+|   |-- split
+|   |   |-- train.json
+|   |   |-- test.json
+|   |   |-- val.json
+|-- config.py
+|-- dataset.py
+|-- model.py
+|-- requirements.txt
+|-- README.md
+|-- test_generation.py
+|-- test_score.py
+|-- train.py
+```
+
+### 3. Run Inference
+
+The `LongT2IExpert` provides two main inference tasks: Long T2I Alignment Scoring and Long T2I Alignment Interpreting.
+
+##### Long T2I Alignment Scoring
+
+```
+python test_score.py
+```
+
+##### Long T2I Alignment Interpreting
+
+```
+python test_generation.py
+```
+
+### 4. Run Training
+
+You can run this code to train <strong>[LongT2IExpert]</strong> from start to finish. 
+
+Make sure the initially untrained weights are located at ``./weights/Qwen2.5-VL-7B-Instruct`` :
+
+You can download the untrained weights from the following link [**(Baidu Netdisk)**](https://pan.baidu.com/s/17PcO4CvgB6FDHh6JBgM_Lg?pwd=3h8m)
+
+```bash
+python train.py
+```
+
+## Citation
+
+If you find this work is useful, pleaes cite our paper!
+
+```bibtex
+@misc{yang2025longt2ibenchbenchmarkevaluatinglong,
+      title={LongT2IBench: A Benchmark for Evaluating Long Text-to-Image Generation with Graph-structured Annotations}, 
+      author={Zhichao Yang and Tianjiao Gu and Jianjie Wang and Feiyu Lin and Xiangfei Sheng and Pengfei Chen and Leida Li},
+      year={2025},
+      eprint={2512.09271},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2512.09271}, 
+}
+```