AI RESEARCH
Stable and Near-Reversible Diffusion ODE Solvers for Image Editing
arXiv CS.LG
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ArXi:2605.16399v1 Announce Type: cross The inversion of diffusion models plays a central role in image editing. Algebraically reversible ODE solvers provide an appealing approach to diffusion inversion for text-guided image editing, by eliminating the inversion error inherent in DDIM-based editing pipelines. However, empirical results indicate that reversibility alone is insufficient. As edits require larger semantic or visual changes, reversible diffusion solvers often exhibit instabilities and suffer sharp drops in output quality.