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@@ -104,6 +104,36 @@ We evaluated this checkpoint in the Imgsys public benchmark. MaPO was able to ou
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  <img src="https://mapo-t2i.github.io/static/images/imgsys.png" width=750/>
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  </div>
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  ## Inference
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  <img src="https://mapo-t2i.github.io/static/images/imgsys.png" width=750/>
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  </div>
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+ The table below reports memory efficiency of MaPO, making it a better alternative for alignment fine-tuning of diffusion models:
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+
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+ <table>
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+ <caption>Computational costs of Diffusion-DPO and MaPO</caption>
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+ <thead>
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+ <tr>
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+ <th></th>
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+ <th>Diffusion-DPO</th>
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+ <th>MaPO <span class="ours">(Ours)</span></th>
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+ </tr>
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+ </thead>
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+ <tbody>
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+ <tr>
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+ <td>Time (↓)</td>
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+ <td>63.5</td>
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+ <td>54.3 (-14.5%)</td>
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+ </tr>
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+ <tr>
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+ <td>GPU Mem. (↓)</td>
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+ <td>55.9</td>
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+ <td>46.1 (-17.5%)</td>
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+ </tr>
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+ <tr>
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+ <td>Max Batch (↑)</td>
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+ <td>4</td>
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+ <td>16 (×4)</td>
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+ </tr>
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+ </tbody>
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+ </table>
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+
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  ## Inference
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