✨Flow Map Distillation Without Data
📝 Summary:
This paper introduces a data-free framework for flow map distillation, eliminating the need for external datasets. By sampling only from the prior distribution, it avoids data mismatch risks and achieves state-of-the-art fidelity with minimal sampling steps, surpassing all data-based alternatives.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19428
• PDF: https://arxiv.org/pdf/2511.19428
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For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#FlowMapDistillation #DataFreeLearning #MachineLearning #DeepLearning #AIResearch
📝 Summary:
This paper introduces a data-free framework for flow map distillation, eliminating the need for external datasets. By sampling only from the prior distribution, it avoids data mismatch risks and achieves state-of-the-art fidelity with minimal sampling steps, surpassing all data-based alternatives.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19428
• PDF: https://arxiv.org/pdf/2511.19428
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#FlowMapDistillation #DataFreeLearning #MachineLearning #DeepLearning #AIResearch