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@@ -513,7 +513,7 @@ <h3 class="title is-5 mt-5 pt-5">3. Real-World Dual-Arm Grasp Results</h3>
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retraining. Finally, real-world experiments on unseen objects such as trays, buckets, and pans
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demonstrate consistent success, confirming that DAGDiff’s classifier-guided diffusion produces grasps
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that are stable, collision-free, and transferable beyond simulation. Real-life failures occur mostly due to noisy point-cloud estimation and
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hance generated grasps are not always perfect.
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hance generated grasps in these cases are not always perfect.
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</div>
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</div>
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</section>

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