Rectify Then Diffuse: Disentangling Concepts Before Denoising Trajectory Unfolds
Quick summary
arXiv:2608.03135v1 Announce Type: cross Abstract: Text-to-image diffusion models can generate individual concepts well, but they often omit or merge concepts incorrectly with multiple concepts. We trace these failures to an early coordination bottleneck: before denoising begins, prompt-conditioned attention may allocate different concepts to strongly overlapping spatial support, which can keep their attention coupled as denoising proceeds. This observation motivates treating compositional generation as a boundary-condition problem rather than repeatedly controlling the evolving trajectory. To
Key takeaways
- arXiv:2608.03135v1 Announce Type: cross Abstract: Text-to-image diffusion models can generate individual concepts well, but they often omit or merge concepts incorrectly with multiple concepts.
- We trace these failures to an early coordination bottleneck: before denoising begins, prompt-conditioned attention may allocate different concepts to strongly overlapping spatial support, which can keep their attention coupled as denoising proceeds.
- This observation motivates treating compositional generation as a boundary-condition problem rather than repeatedly controlling the evolving trajectory.
Why it matters
The importance of “Rectify Then Diffuse: Disentangling Concepts Before Denoising Trajectory Unfolds” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.
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