Update README.md

README.md

@@ -76,7 +76,7 @@ pip install flash_attn==2.5.8 --no-build-isolation
 
 ## Data and base model preparation
 
-1. Download our **22K refined single-candidate data** and **35K multi-candidate data** from [Scone-S2I-57K](https://huggingface.co/datasets/Ryann829/Scone-S2I-57K). The 70K base single-canididate data are sampled from open-source datasets like [X2I](https://huggingface.co/datasets/yzwang/X2I-subject-driven), [MUSAR-Gen](https://huggingface.co/datasets/guozinan/MUSAR-Gen), [UNO-1M](https://huggingface.co/datasets/bytedance-research/UNO-1M), and [Echo-4o-Image](https://huggingface.co/datasets/Yejy53/Echo-4o-Image). Please refer to the dataset links for more details.
+1. Download our **22K refined single-candidate data** and **35K multi-candidate data** from [Scone-S2I-57K](https://huggingface.co/datasets/Ryann829/Scone-S2I-57K). The 70K base single-candidate data are sampled from open-source datasets like [X2I](https://huggingface.co/datasets/yzwang/X2I-subject-driven), [MUSAR-Gen](https://huggingface.co/datasets/guozinan/MUSAR-Gen), [UNO-1M](https://huggingface.co/datasets/bytedance-research/UNO-1M), and [Echo-4o-Image](https://huggingface.co/datasets/Yejy53/Echo-4o-Image). Please refer to the dataset links for more details.
 
    ```bash
    cd Scone
@@ -365,232 +365,6 @@ bash scripts/inference_single_case.sh
 > - To mitigate randomness, we perform 3 rounds of sampling at 1024x1024 resolution, scoring 3 times per round, yielding 9 group results. The final score is the average of these results.
 
 
-## SconeEval benchmark
-<table border="1" style="border-collapse: collapse; width: 100%;">
-    <thead>
-        <tr>
-            <th rowspan="3">Method</th>
-            <th colspan="2">Composition ↑</th>
-            <th colspan="4">Distinction ↑</th>
-            <th colspan="4">Distinction & Composition ↑</th>
-            <th colspan="3">Average ↑</th>
-        </tr>
-        <tr>
-            <th>Single</th>
-            <th>Multi</th>
-            <th colspan="2">Cross</th>
-            <th colspan="2">Intra</th>
-            <th colspan="2">Cross</th>
-            <th colspan="2">Intra</th>
-            <th rowspan="2">COM</th>
-            <th rowspan="2">DIS</th>
-            <th rowspan="2">Overall</th>
-        </tr>
-        <tr>
-            <th>COM</th>
-            <th>COM</th>
-            <th>COM</th>
-            <th>DIS</th>
-            <th>COM</th>
-            <th>DIS</th>
-            <th>COM</th>
-            <th>DIS</th>
-            <th>COM</th>
-            <th>DIS</th>
-        </tr>
-    </thead>
-    <tbody>
-        <tr>
-            <td colspan="14" style="background-color: #ffefe6; text-align: center; font-weight: bold; font-style: italic;">Closed-Source Model</td>
-        </tr>
-        <tr>
-            <td>Gemini-2.5-Flash-Image</td>
-            <td>8.87</td>
-            <td>7.94</td>
-            <td>9.12</td>
-            <td><strong>9.15</strong></td>
-            <td>9.00</td>
-            <td>8.50</td>
-            <td>8.27</td>
-            <td><strong>8.87</strong></td>
-            <td>8.17</td>
-            <td>8.85</td>
-            <td>8.56</td>
-            <td>8.84</td>
-            <td>8.70</td>
-        </tr>
-        <tr>
-            <td>GPT-4o<sup>*</sup></td>
-            <td><strong>8.92</strong></td>
-            <td><strong>8.51</strong></td>
-            <td><strong>9.18</strong></td>
-            <td>8.55</td>
-            <td><strong>9.45</strong></td>
-            <td><strong>9.01</strong></td>
-            <td><strong>8.83</strong></td>
-            <td>8.49</td>
-            <td><strong>8.99</strong></td>
-            <td><strong>9.56</strong></td>
-            <td><strong>8.98</strong></td>
-            <td><strong>8.90</strong></td>
-            <td><strong>8.94</strong></td>
-        </tr>
-        <tr>
-            <td colspan="14" style="background-color: #e0eef9; text-align: center; font-weight: bold; font-style: italic;">Generation Model</td>
-        </tr>
-        <tr>
-            <td>FLUX.1 Kontext [dev]</td>
-            <td>7.92</td>
-            <td>-</td>
-            <td>7.93</td>
-            <td>8.45</td>
-            <td>6.20</td>
-            <td>6.11</td>
-            <td>-</td>
-            <td>-</td>
-            <td>-</td>
-            <td>-</td>
-            <td>-</td>
-            <td>-</td>
-            <td>-</td>
-        </tr>
-        <tr>
-            <td>USO</td>
-            <td>8.03</td>
-            <td>5.19</td>
-            <td>7.96</td>
-            <td>8.50</td>
-            <td>7.14</td>
-            <td>6.51</td>
-            <td>5.10</td>
-            <td>6.25</td>
-            <td>5.07</td>
-            <td>5.57</td>
-            <td>6.41</td>
-            <td>6.71</td>
-            <td>6.56</td>
-        </tr>
-        <tr>
-            <td>UNO</td>
-            <td>7.53</td>
-            <td>5.38</td>
-            <td>7.27</td>
-            <td>7.90</td>
-            <td>6.76</td>
-            <td>6.53</td>
-            <td>5.27</td>
-            <td>7.02</td>
-            <td>5.61</td>
-            <td>6.27</td>
-            <td>6.31</td>
-            <td>6.93</td>
-            <td>6.62</td>
-        </tr>
-        <tr>
-            <td>UniWorld-V2<br>(Edit-R1-Qwen-Image-Edit-2509)</td>
-            <td>8.41</td>
-            <td><strong>7.16</strong></td>
-            <td>8.63</td>
-            <td>8.24</td>
-            <td><strong>7.44</strong></td>
-            <td>6.77</td>
-            <td>7.52</td>
-            <td>8.03</td>
-            <td><strong>7.70</strong></td>
-            <td><strong>7.24</strong></td>
-            <td><strong>7.81</strong></td>
-            <td>7.57</td>
-            <td>7.69</td>
-        </tr>
-        <tr>
-            <td>Qwen-Image-Edit-2509</td>
-            <td><strong>8.54</strong></td>
-            <td>6.85</td>
-            <td><strong>8.85</strong></td>
-            <td><strong>8.57</strong></td>
-            <td>7.32</td>
-            <td><strong>6.86</strong></td>
-            <td><strong>7.53</strong></td>
-            <td><strong>8.13</strong></td>
-            <td>7.49</td>
-            <td>7.02</td>
-            <td>7.76</td>
-            <td><strong>7.65</strong></td>
-            <td><strong>7.70</strong></td>
-        </tr>
-        <tr>
-            <td colspan="14" style="background-color: #E6E6FA; text-align: center; font-weight: bold; font-style: italic;">Unified Model</td>
-        </tr>
-        <tr>
-            <td>BAGEL</td>
-            <td>7.14</td>
-            <td>5.55</td>
-            <td>7.49</td>
-            <td>7.95</td>
-            <td>6.93</td>
-            <td>6.21</td>
-            <td>6.44</td>
-            <td>7.38</td>
-            <td>6.87</td>
-            <td>7.27</td>
-            <td>6.74</td>
-            <td>7.20</td>
-            <td>6.97</td>
-        </tr>
-        <tr>
-            <td>OmniGen2</td>
-            <td>8.00</td>
-            <td>6.59</td>
-            <td>8.31</td>
-            <td>8.99</td>
-            <td>6.99</td>
-            <td>6.80</td>
-            <td>7.28</td>
-            <td>8.30</td>
-            <td>7.14</td>
-            <td>7.13</td>
-            <td>7.39</td>
-            <td>7.81</td>
-            <td>7.60</td>
-        </tr>
-        <tr>
-            <td>Echo-4o</td>
-            <td><strong>8.58</strong></td>
-            <td><strong>7.73</strong></td>
-            <td>8.36</td>
-            <td>8.33</td>
-            <td>7.74</td>
-            <td>7.18</td>
-            <td>7.87</td>
-            <td>8.72</td>
-            <td>8.01</td>
-            <td>8.33</td>
-            <td>8.05</td>
-            <td>8.14</td>
-            <td>8.09</td>
-        </tr>
-        <tr>
-            <td><strong>Scone (Ours)</strong></td>
-            <td>8.52</td>
-            <td>7.40</td>
-            <td><strong>8.98</strong></td>
-            <td><strong>9.73</strong></td>
-            <td><strong>7.97</strong></td>
-            <td><strong>7.74</strong></td>
-            <td><strong>8.20</strong></td>
-            <td><strong>9.25</strong></td>
-            <td><strong>8.21</strong></td>
-            <td><strong>8.44</strong></td>
-            <td><strong>8.21</strong></td>
-            <td><strong>8.79</strong></td>
-            <td><strong>8.50</strong></td>
-        </tr>
-    </tbody>
-</table>
-
-> - *: GPT-4o responded to 365~370 test cases out of the total 409 cases due to OpenAI safety restrictions.
-> - To mitigate randomness, we perform 3 rounds of sampling at 1024x1024 resolution, scoring 3 times per round, yielding 9 group results. The final score is the average of these results.
-
 
 ## SconeEval benchmark
 <p align="center">
@@ -875,14 +649,11 @@ If you find Scone helpful, please consider giving the repo a star ⭐.
 
 If you find this project useful for your research, please consider citing our paper:
 ```bibtex
-@misc{wang2025sconebridgingcompositiondistinction,
-      title={Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling}, 
-      author={Yuran Wang and Bohan Zeng and Chengzhuo Tong and Wenxuan Liu and Yang Shi and Xiaochen Ma and Hao Liang and Yuanxing Zhang and Wentao Zhang},
-      year={2025},
-      eprint={2512.12675},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV},
-      url={https://arxiv.org/abs/2512.12675}, 
+@article{wang2025scone,
+  title={Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling},
+  author={Wang, Yuran and Zeng, Bohan and Tong, Chengzhuo and Liu, Wenxuan and Shi, Yang and Ma, Xiaochen and Liang, Hao and Zhang, Yuanxing and Zhang, Wentao},
+  journal={arXiv preprint arXiv:2512.12675},
+  year={2025}
 }
 ```