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cs.CV2026
FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer
Shenghe Zheng, Minyu Zhang, Tianhao Liu +1
With the growing availability of open-sourced adapters trained on the same diffusion backbone for diverse scenes and objects, combining these pretrained weights enables low-cost cu…
cs.CV2025★ 1 cited
Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging
Shenghe Zheng, Hongzhi Wang, Chenyu Huang +5
With more open-source models available for diverse tasks, model merging has gained attention by combining models into one, reducing training, storage, and inference costs. Current…
cs.CV2024★ 1 cited
FREE-Merging: Fourier Transform for Efficient Model Merging
Shenghe Zheng, Hongzhi Wang
With the rapid growth of deep learning, there is an increasing availability of open-source models for various tasks. However, single fine-tuned models often fall short of meeting t…