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@@ -111,7 +111,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td><b>Average</b> </td>
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  </tr>
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  <tr>
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- <th>Claude3 Opus</th>
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  <td>15.1 </td>
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  <td>33.4 </td>
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  <td>40.6 </td>
@@ -124,7 +124,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>25.7 </td>
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  </tr>
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  <tr>
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- <th>Gemini Ultra</th>
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  <td>14.7 </td>
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  <td>32.3 </td>
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  <td>40.0 </td>
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  <td>23.2 </td>
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  </tr>
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  <tr>
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- <th>GPT-4V</th>
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  <td>11.5 </td>
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  <td>31.5 </td>
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  <td>40.4 </td>
@@ -150,7 +150,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>22.0 </td>
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  </tr>
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  <tr>
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- <th>QwenVL Max</th>
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  <td>7.7 </td>
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  <td>31.4 </td>
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  <td>37.6 </td>
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  <td>21.1 </td>
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  </tr>
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  <tr>
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- <th>Claude3 Sonnet</th>
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  <td>10.5 </td>
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  <td>28.9 </td>
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  <td>35.6 </td>
@@ -176,7 +176,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>21.1 </td>
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  </tr>
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  <tr>
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- <th>QwenVL Plus</th>
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  <td>4.8 </td>
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  <td>28.8 </td>
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  <td>33.7 </td>
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  <td>17.8 </td>
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  </tr>
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  <tr>
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- <th>MiniCPM-Llama3-V-2_5</th>
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  <td>6.1 </td>
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  <td>29.6 </td>
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  <td>35.7 </td>
@@ -202,7 +202,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>17.3 </td>
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  </tr>
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  <tr>
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- <th>InternVL-V1.5</th>
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  <td>3.4 </td>
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  <td>27.1 </td>
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  <td>31.4 </td>
@@ -215,7 +215,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>14.9 </td>
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  </tr>
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  <tr>
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- <th>GLM4V</th>
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  <td>0.3 </td>
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  <td>30.0 </td>
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  <td>34.1 </td>
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  <td>13.6 </td>
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  </tr>
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  <tr>
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- <th>TextSquare</th>
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  <td>3.7 </td>
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  <td>27.0 </td>
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  <td>30.8 </td>
@@ -241,7 +241,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>13.6 </td>
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  </tr>
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  <tr>
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- <th>Mini-Gemini-HD-34B</th>
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  <td>2.2 </td>
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  <td>25.0 </td>
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  <td>29.2 </td>
@@ -254,7 +254,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>13.0 </td>
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  </tr>
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  <tr>
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- <th>InternLM-Xcomposer2-4KHD</th>
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  <td>2.0 </td>
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  <td>20.6 </td>
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  <td>23.2 </td>
@@ -267,7 +267,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>11.2 </td>
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  </tr>
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  <tr>
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- <th>Llava-Next-34B</th>
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  <td>3.3 </td>
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  <td>24.0 </td>
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  <td>28.0 </td>
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  <td>11.1 </td>
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  </tr>
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  <tr>
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- <th>TextMonkey</th>
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  <td>2.0 </td>
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  <td>18.1 </td>
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  <td>19.9 </td>
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  <td>9.9 </td>
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  </tr>
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  <tr>
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- <th>MiniCPM-V-2</th>
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  <td>1.3 </td>
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  <td>12.7 </td>
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  <td>14.9 </td>
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  <td>7.4 </td>
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  </tr>
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  <tr>
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- <th>mPLUG-DocOwl 1.5</th>
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  <td>1.0 </td>
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  <td>13.9 </td>
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  <td>14.9 </td>
@@ -319,7 +319,7 @@ The dataset is oriented toward visual question answering of multilingual text sc
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  <td>7.2 </td>
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  </tr>
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  <tr>
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- <th>YI-VL-34B</th>
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  <td>1.7 </td>
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  <td>13.5 </td>
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  <td>15.7 </td>
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  <td>6.8 </td>
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  </tr>
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  <tr>
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- <th>DeepSeek-VL</th>
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  <td>0.6 </td>
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  <td>14.2 </td>
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  <td>15.3 </td>
 
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  <td><b>Average</b> </td>
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  </tr>
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  <tr>
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+ <th align="left">Claude3 Opus</th>
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  <td>15.1 </td>
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  <td>33.4 </td>
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  <td>40.6 </td>
 
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  <td>25.7 </td>
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  </tr>
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  <tr>
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+ <th align="left">Gemini Ultra</th>
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  <td>14.7 </td>
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  <td>32.3 </td>
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  <td>40.0 </td>
 
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  <td>23.2 </td>
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  </tr>
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  <tr>
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+ <th align="left">GPT-4V</th>
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  <td>11.5 </td>
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  <td>31.5 </td>
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  <td>40.4 </td>
 
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  <td>22.0 </td>
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  </tr>
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  <tr>
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+ <th align="left">QwenVL Max</th>
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  <td>7.7 </td>
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  <td>31.4 </td>
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  <td>37.6 </td>
 
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  <td>21.1 </td>
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  </tr>
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  <tr>
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+ <th align="left">Claude3 Sonnet</th>
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  <td>10.5 </td>
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  <td>28.9 </td>
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  <td>35.6 </td>
 
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  <td>21.1 </td>
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  </tr>
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  <tr>
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+ <th align="left">QwenVL Plus</th>
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  <td>4.8 </td>
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  <td>28.8 </td>
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  <td>33.7 </td>
 
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  <td>17.8 </td>
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  </tr>
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  <tr>
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+ <th align="left">MiniCPM-Llama3-V-2_5</th>
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  <td>6.1 </td>
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  <td>29.6 </td>
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  <td>35.7 </td>
 
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  <td>17.3 </td>
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  </tr>
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  <tr>
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+ <th align="left">InternVL-V1.5</th>
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  <td>3.4 </td>
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  <td>27.1 </td>
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  <td>31.4 </td>
 
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  <td>14.9 </td>
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  </tr>
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  <tr>
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+ <th align="left">GLM4V</th>
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  <td>0.3 </td>
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  <td>30.0 </td>
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  <td>34.1 </td>
 
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  <td>13.6 </td>
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  </tr>
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  <tr>
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+ <th align="left">TextSquare</th>
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  <td>3.7 </td>
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  <td>27.0 </td>
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  <td>30.8 </td>
 
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  <td>13.6 </td>
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  </tr>
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  <tr>
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+ <th align="left">Mini-Gemini-HD-34B</th>
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  <td>2.2 </td>
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  <td>25.0 </td>
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  <td>29.2 </td>
 
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  <td>13.0 </td>
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  </tr>
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  <tr>
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+ <th align="left">InternLM-Xcomposer2-4KHD</th>
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  <td>2.0 </td>
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  <td>20.6 </td>
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  <td>23.2 </td>
 
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  <td>11.2 </td>
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  </tr>
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  <tr>
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+ <th align="left">Llava-Next-34B</th>
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  <td>3.3 </td>
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  <td>24.0 </td>
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  <td>28.0 </td>
 
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  <td>11.1 </td>
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  </tr>
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  <tr>
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+ <th align="left">TextMonkey</th>
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  <td>2.0 </td>
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  <td>18.1 </td>
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  <td>19.9 </td>
 
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  <td>9.9 </td>
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  </tr>
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  <tr>
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+ <th align="left">MiniCPM-V-2</th>
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  <td>1.3 </td>
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  <td>12.7 </td>
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  <td>14.9 </td>
 
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  <td>7.4 </td>
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  </tr>
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  <tr>
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+ <th align="left">mPLUG-DocOwl 1.5</th>
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  <td>1.0 </td>
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  <td>13.9 </td>
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  <td>14.9 </td>
 
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  <td>7.2 </td>
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  </tr>
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  <tr>
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+ <th align="left">YI-VL-34B</th>
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  <td>1.7 </td>
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  <td>13.5 </td>
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  <td>15.7 </td>
 
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  <td>6.8 </td>
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  </tr>
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  <tr>
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+ <th align="left">DeepSeek-VL</th>
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  <td>0.6 </td>
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  <td>14.2 </td>
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  <td>15.3 </td>