Rethinking Cross-Layer Information Routing in Diffusion Transformers
Diffusion Transformers use standard residual connections that cause information flow issues like magnitude inflation and redundancy across layers. The authors introduced Diffusion-Adaptive Routing (DAR), a new method that uses learnable, timestep-adaptive aggregation to control which past layer outputs are combined. This improves model convergence speed and final image quality.