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Bootstrap Your Generator (ByG) is a framework for unpaired training of flow matching editing models, leveraging base model knowledge and gradient routing to achieve state-of-the-art results in data-scarce image and video editing tasks.
This paper proposes a Mixture of LoRA and Full (MoLF) fine-tuning framework that uses gradient-guided optimizer routing to adaptively switch between LoRA and full fine-tuning. It aims to overcome the structural limitations of relying solely on static adaptation methods by combining the plasticity of full tuning with the regularization of LoRA.