Bezier Distillation

• URL: http://arxiv.org/abs/2503.16562v1
• Date: Thu, 20 Mar 2025 06:48:35 GMT
• Title: Bezier Distillation
• Authors: Ling Feng, SK Yang,
• Abstract summary: In Rectified Flow, by obtaining the rectified flow several times, the mapping relationship between distributions can be distilled into a neural network.<n>I intend to combine multi - teacher knowledge distillation with Bezier curves to solve the problem of error accumulation.
• Score: 5.432285843497807
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In Rectified Flow, by obtaining the rectified flow several times, the mapping relationship between distributions can be distilled into a neural network, and the target distribution can be directly predicted by the straight lines of the flow. However, during the pairing process of the mapping relationship, a large amount of error accumulation will occur, resulting in a decrease in performance after multiple rectifications. In the field of flow models, knowledge distillation of multi - teacher diffusion models is also a problem worthy of discussion in accelerating sampling. I intend to combine multi - teacher knowledge distillation with Bezier curves to solve the problem of error accumulation. Currently, the related paper is being written by myself.

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