Pretrained Diffusion Transformers (DiTs) possess an intrinsic 'synchronization gap' where different features commit at specific, depth-localized layers.
March 24, 2026
Original Paper
Interpreting the Synchronization Gap: The Hidden Mechanism Inside Diffusion Transformers
arXiv · 2603.20987
The Takeaway
This provides a mechanistic explanation for the reverse diffusion process in DiTs, moving beyond 'black box' generative trajectories. It demonstrates that internal mode commitment is strictly depth-localized in the final layers, offering a blueprint for more efficient sampling and architectural optimization.
From the abstract
Recent theoretical models of diffusion processes, conceptualized as coupled Ornstein-Uhlenbeck systems, predict a hierarchy of interaction timescales, and consequently, the existence of a synchronization gap between modes that commit at different stages of the reverse process. However, because these predictions rely on continuous time and analytically tractable score functions, it remains unclear how this phenomenology manifests in the deep, discrete architectures deployed in practice. In this w