AI RESEARCH
Exploring Data-Free LoRA Transferability for Video Diffusion Models
arXiv CS.CV
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ArXi:2605.01929v1 Announce Type: new Video diffusion models leveraging step distillation or causal distillation have achieved remarkable performance. However, adapting existing LoRAs to these variants remains a critical challenge due to weight space mismatches. We observe that direct application leads to style degradation and structural collapse, yet the underlying mechanisms remain poorly understood. To fill this gap, we delve into the weight space and identify that the incompatibility stems from spectral interference within shared functional clusters defined over singular subspaces.